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 .
Response to Amendment
The claims filed 01/30/2026 has been entered.
Claims 1-15 are pending.
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.
Claims 1-4 and 13-15 are rejected under 35 U.S.C. 103 as being unpatentable over Wang (US 20220035029 A1), or Schumann (DE 102018218007 A1) or Gotzig (DE10151965A1) in view of Blanco (US 5323647 A1).
Regarding claim 1, Wang teaches A method for estimating the a height of an object by ultrasonic sensor technology of a vehicle[Fig 2 shows object at height h in front of vehicle], comprising
a) receiving, at a computer of a vehicle, at least two ultrasonic signals by at least one ultrasonic sensor, wherein a single ultrasonic sensor has different sensor positions relative to the object due to vehicle movement or wherein multiple ultrasonic sensors have different sensor positions relative to the object due to at least one of the vehicle movement or a different arrangement on the vehicle[Sensors #30 and #35 in fig 3 and #30 in Fig 2 are ultrasonic sensors sensing objects from different positions. See Abstract; 0029-0032];
b) calculating by the computer, a first item of height information which is a measure of the a squared height of the object, based on two items of spacing information measured between the respective sensor position and the object, and an item of distance information measured horizontally between the sensor positions[Fig 2 shows distance between sensors S and distances d1 and d2 and calculation of risk of collision based on dimensions; See 0012 has collision evaluation based on height meaning there is triangulation based on math and Pythagoras theorem which would involve squaring of variables];…..
d) receiving, at the computer, at least one further ultrasonic signal by the at least one ultrasonic sensor and calculating a second item of height information which is a measure of the squared height of the object, based on two items of spacing information measured between the respective sensor position corresponding to the further ultrasonic signal and the object, and an item of distance formation measured horizontally between the sensor positions corresponding to the further ultrasonic signal[ Sensors #30 and #35 in fig 3 and #30 in Fig 2 are ultrasonic sensors sensing objects from different positions. See Abstract; 0029-0032 as well as Fig 2 shows distance between sensors and distances d1 and d2 and calculation of risk of collision based on dimensions; See 0012 has collision evaluation based on height meaning there is triangulation based on math and Pythagoras theorem which would involve squaring of variables as well as duplication of measurements]…
Schumann teaches A method for estimating the a height of an object by ultrasonic sensor technology of a vehicle[Fig 2 shows object at height h in front of vehicle], comprising :
a) receiving, at a computer of a vehicle, at least two ultrasonic signals by at least one ultrasonic sensor, wherein a single ultrasonic sensor has different sensor positions relative to the object due to vehicle movement or wherein multiple ultrasonic sensors have different sensor positions relative to the object due to at least one of the vehicle movement or a different arrangement on the vehicle[Sensors #12 and #12 in fig 2 are ultrasonic sensors sensing object height X from different positions. See Abstract;];
b) calculating by the computer, a first item of height information which is a measure of the a squared height of the object, based on two items of spacing information measured between the respective sensor position and the object, and an item of distance information measured horizontally between the sensor positions[Fig 2 shows distance between sensors dh and distances d1 and d2 and object height h. See 0010 for formula which has squaring and based on spacing of sensor position and distance]; …..
d) receiving, at the computer, at least one further ultrasonic signal by the at least one ultrasonic sensor and calculating a second item of height information which is a measure of the squared height of the object, based on two items of spacing information measured between the respective sensor position corresponding to the further ultrasonic signal and the object, and an item of distance information measured horizontally between the sensor positions corresponding to the further ultrasonic signal[ Sensors # 12 and 12 in fig 2 are ultrasonic sensors sensing object height X from different positions. See Abstract; Fig 2 shows distance between sensors dh and distances d1 and d2 and object height h. See 0010 for formula which has squaring and based on spacing of sensor position and distances well as duplication of measurements]…
Gotzig teaches A method for estimating the a height of an object by ultrasonic sensor technology of a vehicle [Fig 1 shows object at height ZA in front of vehicle], comprising :
a) receiving, at a computer of a vehicle, at least two ultrasonic signals by at least one ultrasonic sensor, wherein a single ultrasonic sensor has different sensor positions relative to the object due to vehicle movement or wherein multiple ultrasonic sensors have different sensor positions relative to the object due to at least one of the vehicle movement or a different arrangement on the vehicle[Sensors #S1 and #S2 in fig 1 are ultrasonic sensors sensing object height ZA from different positions. See Abstract, Claim 1;];
b) calculating by the computer, a first item of height information which is a measure of the a squared height of the object, based on two items of spacing information measured between the respective sensor position and the object, and an item of distance information measured horizontally between the sensor positions[Fig 1 shows distance between sensors delataF and distances r1A and r2A and object height Za. See Claim 1, 2 for formula which has squaring and based on spacing of sensor position and distance];…..
d) receiving, at the computer, at least one further ultrasonic signal by the at least one ultrasonic sensor and calculating a second item of height information which is a measure of the squared height of the object, based on two items of spacing information measured between the respective sensor position corresponding to the further ultrasonic signal and the object, and an item of distance information measured horizontally between the sensor positions corresponding to the further ultrasonic signal[ Sensors #S1 and #S2 in fig 1 are ultrasonic sensors sensing object height ZA from different positions. See Abstract, Claim 1; Fig 1 shows distance between sensors delataF and distances r1A and r2A and object height Za. See Claim 1, 2 for formula which has squaring and based on spacing of sensor position and distance as well as duplication of measurements]…
Neither Wang, Schumann or Gotzig explicitly teaches c) calculating, by the computer, a variance of first item of height information; ;e) calculating, by the computer, the variance of the second item of height information; f) calculating, by the computer, an averaged item of height information by combining the first item of height information and the second item of height information, and an averaged variance of the height information by combining the variance of the first item of height information and the variance of the second item of height information; g) classifying, by the computer, the object in a height class by calculating, by the computer, at least one probability value based on a normal distribution function which has as a mean value the averaged item of height information and as the a variance the averaged variance of the height information.
Blanco teaches c) calculating, by the computer, a variance of first item of height information[ 7; Lines 40-65 have variance calculation of height];
e) calculating, by the computer, the variance of the second item of height information[Col 7; Lines 40-65 have variance calculation of height];
f) calculating, by the computer, an averaged item of height information by combining the first item of height information and the second item of height information, and an averaged variance of the height formation by combining the variance of the first item of height in formation and the variance of the second item of height information [Col 7 Lines 20-45 have averaging of height and variance];
g) classifying, by the computer, the object in a height class by calculating, by the computer, at least one probability value based on a normal distribution function which has as a mean value the averaged item of height information and as the a variance the averaged variance of the height information 7 Lines 20-45 have averaging of height and variance].
It would have been obvious to one of ordinary skill in the art before the filing date to have modified the sensor in Wang or Schumann or Gotzig with the variance and calculation of Blanco to more accurately account for variance, errors and average out the height.
Regarding claim 15, Wang teaches A system for estimating a height of an object utilizing ultrasonic sensor technology provided on a vehicle and comprising a computer [Fig 2 shows object at height h in front of vehicle], wherein the system is configured to carry out
a)receiving, by the computer, at least two ultrasonic signals by at least one ultrasonic sensor of the ultrasonic sensor technology, wherein a single ultrasonic sensor has different sensor positions relative to the object due to at least one of vehicle movement or wherein multiple ultrasonic sensors have different sensor positions relative to the object due to at least one of the vehicle movement or a different arrangement on the vehicle[Sensors #30 and #35 in fig 3 and #30 in Fig 2 are ultrasonic sensors sensing objects from different positions. See Abstract; 0029-0032];
b) calculating, by the computer, a first item of height information which is a measure of a squared height of the object, based on two items of spacing information measured between the respective sensor position and the object, and an item of distance information measured horizontally between the sensor positions by the computer unit[Fig 2 shows distance between sensors S and distances dl and d2 and calculation of risk of collision based on dimensions; See 0012 has collision evaluation based on height meaning there is triangulation based on math and Pythagoras theorem which would involve squaring of variables];…..
d) receiving, by the computer, at least one further ultrasonic signal by the at least one ultrasonic sensor and calculating a second item of height information which is a measure of the squared height of the object, based on two items of spacing information measured between the respective sensor position corresponding to the at least one further ultrasonic signal and the object, and an item of distance information measured horizontally between the sensor positions[Sensors #30 and #35 in fig. 3 and #30 in Fig 2 are ultrasonic sensors sensing objects from different positions. See Abstract; 0029-0032 as well as Fig 2 shows distance between sensors S and distances dl and d2 and calculation of risk of collision based on dimensions; See 0012 has collision evaluation based on height meaning there is triangulation based on math and Pythagoras theorem which would involve squaring of variables as well as duplication of measurements];…
Schumann teaches A system for estimating a height of an object utilizing ultrasonic sensor technology provided on a vehicle and comprising a computer[Fig 2 shows object at height h in front of vehicle], wherein the system is configured to carry out
a)receiving, by the computer, at least two ultrasonic signals by at least one ultrasonic sensor of the ultrasonic sensor technology, wherein a single ultrasonic sensor has different sensor positions relative to the object due to at least one of vehicle movement or wherein multiple ultrasonic sensors have different sensor positions relative to the object due to at least one of the vehicle movement or a different arrangement on the vehicle [Sensors #12 and #12 in fig 2 are ultrasonic sensors sensing object height x from different positions. See Abstract;];
b) calculating, by the computer, a first item of height information which is a measure of a squared height of the object, based on two items of spacing information measured between the respective sensor position and the object, and an item of distance information measured horizontally between the sensor positions by the computer unit[Fig 2 shows distance between sensors dh and distances dl and d2 and object height h. See 0010 for formula which has squaring and based on spacing of sensor position and distance];…..
d) receiving, by the computer, at least one further ultrasonic signal by the at least one ultrasonic sensor and calculating a second item of height information which is a measure of the squared height of the object, based on two items of spacing information measured between the respective sensor position corresponding to the at least one further ultrasonic signal and the object, and an item of distance information measured horizontally between the sensor positions[Sensors #12 and #12 in fig 2 are ultrasonic sensors sensing object height X from different positions. See Abstract; Fig 2 shows distance between sensors dh and distances dl and d2 and object height h. See 0010 for formula which has squaring and based on spacing of sensor position and distances well as duplication of measurements];…
Gotzig teaches A system for estimating a height of an object utilizing ultrasonic sensor technology provided on a vehicle and comprising a computer[Fig 1 shows object at height ZA in front of vehicle], wherein the system is configured to carry out
a)receiving, by the computer, at least two ultrasonic signals by at least one ultrasonic sensor of the ultrasonic sensor technology, wherein a single ultrasonic sensor has different sensor positions relative to the object due to at least one of vehicle movement or wherein multiple ultrasonic sensors have different sensor positions relative to the object due to at least one of the vehicle movement or a different arrangement on the vehicle Sensors #S1 and #S2 in fig 1 are ultrasonic sensors sensing object height ZA from different positions. See Abstract, Claim 1;]
b) calculating, by the computer, a first item of height information which is a measure of a squared height of the object, based on two items of spacing information measured between the respective sensor position and the object, and an item of distance information measured horizontally between the sensor positions by the computer unit[Fig 1 shows distance between sensors delataF and distances r1A and r2A and object height Za. See Claim 1, 2 for formula which has squaring and based on spacing of sensor position and distance];…..
d) receiving, at the computer, at least one further ultrasonic signal by the at least one ultrasonic sensor and calculating a second item of height information which is a measure of the squared height of the object, based on two items of spacing information measured between the respective sensor position corresponding to the at least one further ultrasonic signal and the object, and an item of distance information measured horizontally between the sensor positions[Sensors #S1 and #S2 in fig 1 are ultrasonic sensors sensing object height ZA from different positions. See Abstract, Claim 1; Fig 1 shows distance between sensors delataF and distances r1A and r2A and object height Za. See Claim 1, 2 for formula which has squaring and based on spacing of sensor position and distance as well as duplication of measurements];
Neither Wang, Schumann or Gotzig explicitly teaches c)calculating a variance of the first item of height information by the computer;….. ;e) calculating, by the computer, the variance of the second height information; f) calculating, by the computer, an averaged item of height information by combining the first item of height information and the second item of height information, and an averaged variance of the height information by combining the variance of the first item of height information and the second item of height information; g) classifying, by the computer, the object in a height class by calculating at least one probability value by the computer based on a normal distribution function which has as a mean value the averaged item of height information and as a variance the averaged variance of the height information.
Blanco teaches that c)calculating a variance of the first item of height information by the computer[Col 7; Lines 40-65 have variance calculation of height];…..
e) calculating, by the computer, the variance of the second height information [Col 7; Lines 40-65 have variance calculation of height];
f) calculating, by the computer, an averaged item of height information by combining the first item of height information and the second item of height information, and an averaged variance of the height information by combining the variance of the first item of height formation and the second item of height information [Col 7 Lines 20-45 have averaging of height and variance];
g) classifying, by the computer, the object in a height class by calculating at least one probability value by the computer based on a normal distribution function which has as a mean value the averaged item of height information and as a variance the averaged variance of the height information. [Col 7 Lines 20-45 have averaging of height and variance].
It would have been obvious to one of ordinary skill in the art before the filing date to have modified the sensor in Wang or Schumann or Gotzig with the variance and calculation of Blanco to more accurately account for variance, errors and average out the height.
Regarding claim 2, Neither Wang, Schumann or Gotzig explicitly teaches wherein further items of height information, which are a measure of the squared height of the object, and variance information regarding the further items of height information are calculated iteratively, and that the averaged item of height information is determined by combining the items of height information and the averaged variance of the height information is determined by combining the variances of the height information.
Blanco teaches wherein further items of height information, which are a measure of the squared height of the object, and variance information regarding the further items of height information are calculated iteratively, and that the averaged item of height information is determined by combining the items of height information and the averaged variance of the height information is determined by combining the variances of the height information. [Col 7 Lines 20-45 have averaging of height and variance and running average meaning it is iterative]
It would have been obvious to one of ordinary skill in the art before the filing date to have modified the sensor in Wang or Schumann or Gotzig with the variance and calculation of Blanco to more accurately account for variance, errors and average out the height.
Regarding claim 3, Wang, as modified, teaches wherein at least one of the first, second, or further items of height information are calculated by the following formula:
PNG
media_image1.png
60
246
media_image1.png
Greyscale
wherein the following applies: h: height difference between the at least one ultrasonic sensor and the object; rl: spacing between a first transmitter position and the object in transmitting and receiving direction; r2: spacing between a second transmitter position and the object in a transmitting and receiving direction of the second transmitter position; s: distance information measured in the horizontal direction as the spacing between the first sensor position and the second sensor position. [Fig 2 shows distance between sensors S and distances d1 and d2 and calculation of risk of collision based on dimensions; See 0012 has collision evaluation based on height meaning there is triangulation based on math and Pythagoras theorem which would involve squaring of variables]
Schumann, as modified, teaches wherein at least one of the first, second, or further items of height information are calculated by the following formula:
PNG
media_image1.png
60
246
media_image1.png
Greyscale
wherein the following applies: h: height difference between the at least one ultrasonic sensor and the object; r1: spacing between a first transmitter position and the object in transmitting and receiving direction; r2: spacing between a second transmitter position and the object in a transmitting and receiving direction of the second transmitter position;s: distance information measured in the horizontal direction as the spacing between the first sensor position and the second sensor position. [Fig 2 shows distance between sensors dh and distances d1 and d2 and object height h. See 0010 for formula which has squaring and based on spacing of sensor position and distance]
Gotzig, as modified, teaches wherein at least one of the first, second, or further items of height information are calculated by the following formula:
PNG
media_image1.png
60
246
media_image1.png
Greyscale
wherein the following applies: h: height difference between the at least one ultrasonic sensor and the object; rl: spacing between a first transmitter position and the object in transmitting and receiving direction; r2: spacing between a second transmitter position and the object in a transmitting and receiving direction of the second transmitter position;s: distance information measured in the horizontal direction as the spacing between the first sensor position and the second sensor position. [Fig 1 shows distance between sensors delataF and distances r1A and r2A and object height Za. See Claim 1, 2 for formula which has squaring and based on spacing of sensor position and distance]
Regarding claim 4, Neither Wang, Schumann or Gotzig explicitly teaches wherein wherein the variance of at least one of the first item of height information, the second item of height information, or the further items of height information is established based on a first-order variation analysis.
Blanco teaches wherein the variance of at least one of the first item of height information, the second item of height information, or the further items of height information is established based on a first-order variation analysis. [Col 7 Lines 20-45 have averaging of height and variance]
It would have been obvious to one of ordinary skill in the art before the filing date to have modified the sensor in Wang or Schumann or Gotzig with the variance and calculation of Blanco to more accurately account for variance, errors and average out the height.
Regarding claim 13, Wang, as modified, teaches wherein the object is assumed to be a line object having a longitudinal alignment, and a transmitting and receiving direction of the at least one ultrasonic sensor and a direction in which the distance information is measured is assumed to be perpendicular to the longitudinal alignment of the line object. [Fig 2 has object as described]
Schumann, as modified, teaches wherein the object is assumed to be a line object having a longitudinal alignment, and a transmitting and receiving direction of the at least one ultrasonic sensor and a direction in which the distance information is measured is assumed to be perpendicular to the longitudinal alignment of the line object. [Fig 2 has object as described]
Gotzig, as modified, teaches wherein the object is assumed to be a line object having a longitudinal alignment, and a transmitting and receiving direction of the at least one ultrasonic sensor and a direction in which the distance information is measured is assumed to be perpendicular to the longitudinal alignment of the line object. [Fig 1 has object as described]
Regarding claim 14, Wang, as modified, teaches wherein the object is simulated by items of information, which were established by ultrasonic sensor technology in multiple capturing cycles, by an object contour line, and the items of distance information are assumed to be a difference between a horizontally measured spacing of the sensor positions and the object contour line. [Description at 0010-0016 has collision evaluation meaning simulation]
Schumann, as modified, teaches wherein the object is simulated by items of information, which were established by ultrasonic sensor technology in multiple capturing cycles, by an object contour line, and the items of distance information are assumed to be a difference between a horizontally measured spacing of the sensor positions and the object contour line. [Description has collision evaluation meaning simulation]
Gotzig, as modified, teaches wherein the object is simulated by items of information, which were established by ultrasonic sensor technology in multiple capturing cycles, by an object contour line, and the items of distance information are assumed to be a difference between a horizontally measured spacing of the sensor positions and the object contour line. [Description has collision evaluation meaning simulation]
Claims 5, and 9-12 are rejected under 35 U.S.C. 103 as being unpatentable over Wang (US 20220035029 A1), or Schumann (DE 102018218007 A1) or Gotzig (DE10151965A1) in view of Blanco (US 5323647 A1) as applied to claims 1 and 2 above, and further in view of Variance(Wikipedia).
Regarding claim 5, The prior art does not explicitly teach wherein the variance of at least one of the first second or further items of height information is calculated by the following wherein the following equation:
PNG
media_image2.png
62
446
media_image2.png
Greyscale
wherein the following applies wherein the following applies:r1: spacing between a first transmitter position and the object in a transmitting and receiving direction; r2: spacing between a second transmitter position and the object in the transmitting and receiving direction; S: distance information measured in the horizontal direction as the spacing between the first and second sensor position;: dH/dr1 first derivative of the height information H according to r1;:dh/dr2 first derivative of the height information H according to r2 dH/ds. first derivative of the height information H according to s;Var[r1]: variance of the spacing between a first transmitter position and the object in the transmitting and receiving direction; Var[r2]: variance of the spacing between a second transmitter position and the object in the transmitting and receiving direction; Var[s]: variance of the distance information measured in the horizontal direction as the spacing between the first and second sensor position.
Wikipedia teaches that wherein the variance of at least one of the first second or further items of height information is calculated by the following equation:
PNG
media_image2.png
62
446
media_image2.png
Greyscale
wherein the following applies wherein the following applies:r1: spacing between a first transmitter position and the object in a transmitting and receiving direction; r2: spacing between a second transmitter position and the object in the transmitting and receiving direction; S: distance information measured in the horizontal direction as the spacing between the first and second sensor position;: dH/dr1 first derivative of the height information H according to r1;:dh/dr2 first derivative of the height information H according to r2 dH/ds. first derivative of the height information H according to s;Var[r1]: variance of the spacing between a first transmitter position and the object in the transmitting and receiving direction; Var[r2]: variance of the spacing between a second transmitter position and the object in the transmitting and receiving direction; Var[s]: variance of the distance information measured in the horizontal direction as the spacing between the first and second sensor position [Wikipedia contains formulas for variance and derivatives of variables as seen in the Discrete random variable or absolutely continuous random variable]
It would have been obvious to one of ordinary skill in the art before the filing date to have modified the sensor in Wang or Schumann or Gotzig with known statistical formulas and methods from Wikipedia in order to calculate variance data.
Regarding claim 9, The prior art does not explicitly teach whererin, the at least one probability value for assigning the object to a height class is calculated based on the following formula
PNG
media_image3.png
62
180
media_image3.png
Greyscale
; wherein the following applies: N(x, H, Var[H]): normal distribution; a: lower limit for allocation to the respective height class; b: upper limit for allocation to the respective height class; H: averaged item of height information; Var[H]: averaged variance of the height information.
Wikipedia teaches that whererin, the at least one probability value for assigning the object to a height class is calculated based on the following formula:
PNG
media_image3.png
62
180
media_image3.png
Greyscale
; wherein the following applies: N(x, H, Var[H]): normal distribution; a: lower limit for allocation to the respective height class; b: upper limit for allocation to the respective height class; H: averaged item of height information; Var[H]: averaged variance of the height information. [Wikipedia contains variance calculations and distribution]
It would have been obvious to one of ordinary skill in the art before the filing date to have modified the sensor in Wang or Schumann or Gotzig with known statistical formulas and methods from Wikipedia in order to calculate variance data.
Regarding claim 10, The prior art does not explicitly teach wherein the height class is calculated based on a correction function which takes into account a deviation of a statistical distribution of the height information from a normal function.
Wikipedia teaches that wherein the height class is calculated based on a correction function which takes into account a deviation of a statistical distribution of the height information from a normal function. [Wikipedia contains deviation such as standard deviation and normal distribution]
It would have been obvious to one of ordinary skill in the art before the filing date to have modified the sensor in Wang or Schumann or Gotzig with known statistical formulas and methods from Wikipedia in order to calculate variance data.
Regarding claim 11, Wang, as modified, teaches wherein the correction function is estimated, based on a stream of height information data which were established based on different items of spacing information between the respective sensor position and the object and different items of horizontally measured distance information [Sensors #30 and #35 in fig 3 and #30 in Fig 2 are ultrasonic sensors sensing objects from different positions. See Abstract; 0029-0032]
Schumann, as modified, teaches wherein the correction function is estimated, based on a stream of height information data which were established based on different items of spacing information between the respective sensor position and the object and different items of horizontally measured distance information[Sensors#12 and #12 in fig 2 are ultrasonic sensors sensing object height X from different positions. See Abstract;]
Gotzig, as modified, teaches wherein the correction function is estimated, based on a stream of height information data which were established based on different items of spacing information between the respective sensor position and the object and different items of horizontally measured distance information[ Sensors #S1 and #S2 in fig 1 are ultrasonic sensors sensing object height ZA from different positions. See Abstract, Claim 1;]
Regarding claim 12, The prior art does not explicitly teach wherein at least one of a lower limit or an upper limit is used for the calculation of the probability value which is adjusted based on the correction function.
Wikipedia teaches that wherein at least one of a lower limit or an upper limit is used for the calculation of the probability value which is adjusted based on the correction function. [Wikipedia has lower and upper limits in distribution calculation]
It would have been obvious to one of ordinary skill in the art before the filing date to have modified the sensor in Wang or Schumann or Gotzig with known statistical formulas and methods from Wikipedia in order to calculate variance data.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Wang (US 20220035029 A1), or Schumann (DE 102018218007 A1) or Gotzig (DE10151965A1) as applied to claim 1 above, and further in view of Weighted average from errors (math.stackexchange).
Regarding claim 6, The prior art does not explicitly teach wherein the averaged item of height information H is calculated based on the following formula:
PNG
media_image4.png
58
238
media_image4.png
Greyscale
wherein the following applies: H': estimated items of height information from a first measuring cycle; H": estimated items of height information from a second measuring cycle; Var[H']: variance of the height information in the first measuring cycle; Var[H"]: variance of the height information in the second measuring cycle.
Math Stack exchange teaches wherein the averaged item of height information H is calculated based on the following formula:
PNG
media_image4.png
58
238
media_image4.png
Greyscale
wherein the following applies: H': estimated items of height information from a first measuring cycle; H": estimated items of height information from a second measuring cycle; Var[H']: variance of the height information in the first measuring cycle; Var[H"]: variance of the height information in the second measuring cycle. [Use of formula on webpage to use weighted average]
It would have been obvious to one of ordinary skill in the art before the filing date to have modified the sensor in Wang or Schumann or Gotzig with known statistical formulas and methods from math stack exchange in order to calculate variance averaged data.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Wang (US 20220035029 A1), or Schumann (DE 102018218007 A1) or Gotzig (DE10151965A1) as applied to claim 1 above, and further in view of random variables (stats.stackexchange).
Regarding claim 7, The prior art does not explicitly teach wherein the averaged variance of the height information H is calculated based on the following formula:
PNG
media_image5.png
66
204
media_image5.png
Greyscale
wherein the following applies: H': estimated items of height information from a first measuring cycle; H": estimated items of height information from a second measuring cycle; Var[H']: variance of the height information in the first measuring cycle; Var[H"]: variance of the height information in the second measuring cycle.
Stats Stack Exchange teaches that wherein the averaged variance of the height information wherein H is calculated based on the following formula:
PNG
media_image5.png
66
204
media_image5.png
Greyscale
wherein the following applies: H': estimated items of height information from a first measuring cycle; H": estimated items of height information from a second measuring cycle; Var[H']: variance of the height information in the first measuring cycle; Var[H"]: variance of the height information in the second measuring cycle. [Use of formula on webpage to use error average using variance]
It would have been obvious to one of ordinary skill in the art before the filing date to have modified the sensor in Wang or Schumann or Gotzig with known statistical formulas and methods from Stats Stack Exchange in order to calculate variance averaged data.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Wang (US 20220035029 A1), or Schumann (DE 102018218007 A1) or Gotzig (DE10151965A1) as applied to claim 1 above, and further in view of Average using least squares (math.stackexchange).
Regarding claim 8, The prior art does not explicitly teach wherein the averaged item of height information and the averaged variance of the height information are calculated based on a least squares method.
Math Stack exchange teaches wherein the averaged item of height information and the averaged variance of the height information are calculated based on a least squares method. [Use of formula on webpage to use error average using variance]
It would have been obvious to one of ordinary skill in the art before the filing date to have modified the sensor in Wang or Schumann or Gotzig with known statistical formulas and methods from Math Stack exchange in order to calculate variance averaged data.
Response to Arguments
Applicant's arguments filed 01/30/2026 have been fully considered but they are not persuasive.
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
Applicant is reading the prior art of Blanco overly narrowly. As stated above the art in Blanco recites variance in first and second height information and Blanco does teach averaging and a person of ordinary skill in the art seeing all the art as a whole would have modified the sensor in Wang or Schumann or Gotzig with the variance and calculation of Blanco to more accurately account for variance, errors and average out the height.
Moreover such steps appear to be regular mathematical and statistical analysis which would be well within the expertise of a person of ordinary skill in the art as it has been held that where routine testing and general experimental conditions are present, discovering the optimum or workable ranges until the desired effect is achieved involves only routine skill in the art. See, In re Aller, 105 USPQ 233.
In response to applicant's argument that Blanco is being used for texture/threshold measure , the fact that the inventor has recognized another advantage which would flow naturally from following the suggestion of the prior art cannot be the basis for patentability when the differences would otherwise be obvious. See Ex parte Obiaya, 227 USPQ 58, 60 (Bd. Pat. App. & Inter. 1985).
Applicant's remaining arguments amount to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references. Rejections are maintained – and no allowable subject matter can be identified at this time.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any 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 VIKAS NMN ATMAKURI whose telephone number is (571)272-5080. The examiner can normally be reached Monday-Friday 7:30am-5:30pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Isam Alsomiri can be reached at (571)272-6970. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/VIKAS ATMAKURI/Examiner, Art Unit 3645
/HELAL A ALGAHAIM/SPE , Art Unit 3645