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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 10/30/2025 has been entered.
Claim Status
This Office Action is in response to communications filed on 10/30/2025. No claims were amended. Claims 3, 8, 20-21, 23-25, 28-34 remain cancelled. Claim 36 was newly added. Claims 1-2, 4-7, 9-19, 22, 26-27, 35 and 36 were pending for examination.
Title 35, U.S. Code
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior office action.
Claim Rejections - 35 USC § 103
Claims 1-2, 4-7, 9-19, 22, 26-27, 35 and 36 are rejected under 35 U.S.C. 103 as being unpatentable over Almalki et al. (U.S. Patent Application Pub. 2017/0138740) in view of Agrawal (U.S. Patent Application Pub. 2020/0019352).
Regarding claim 1 (Previously Presented), Almalki teaches a method, comprising: forming, by a first motion estimator (camera module 153) and a second motion estimator (motion sensor 182), respective first and second estimates of position of a mobile device (mobile device 100) over time based on sensor data generated at the mobile device (¶025; see camera module 153, ¶029-¶038 and motion sensor 182, ¶039-¶042), the first motion estimator having a first reference frame and the second motion estimator having a second reference frame, each of the first and second reference frames being a reference system (first & second pairs of image frames; ¶079-¶080), and each of the first and second estimates of position including one or more estimate components (¶039-¶042, ¶063-¶079, with Fig 6); and
determining a transformation from the second reference frame to the first reference frame based at least in part on at least one estimate component of the one or more estimate components of the first and second estimates of position (¶080; direction of motion of the mobile device may then be determined in operation 610, based on at least one of the first estimated direction and the second estimated direction. In other words, the direction of motion of the mobile device is determined by considering one or both of the analysis of the transformation between consecutive image frames and the motion sensor data obtained by the mobile device. In at least some embodiments, the direction of motion may be calculated by weighting the first estimated direction and the second estimated direction).
Almalki does not explicitly mention each of the first and second reference frames being a reference coordinate system. Agrawal teaches a method, comprising: forming, by a first motion estimator (¶063; a device 108 may determine whether the user/mobile device 105 has entered a geographical location that device 108 is located within … as “geographical location” refers to a building, geofence, or other boundary that identifies a point of interest, device 108 may use a range of GPS coordinates; see full details in (¶061 - ¶064 ) and a second motion estimator (¶063; device 108 may use coordinates based on another reference or measurement frame) included within, or that define a boundary of, the geographical location in which device 108 resides), respective first and second estimates of position of a mobile device over time based on sensor data generated at the mobile device (¶063 - ¶065), the first motiona reference coordinate system (GPS coordinates and coordinates based on another reference or measurement frame are of a reference coordinate system), and each of the first and second estimates of position including one or more estimate components (“geographical location” or one of the GPS coordinates from the range of the GPS coordinates), and determining a transformation from the second reference frame to the first reference frame based at least in part on at least one estimate component of the one or more estimate components of the first and second estimates of position (¶065; if device 108 coordinates were determined with respect to a different reference frame than the coordinates of mobile device 105, device 108 may execute a suitable transform algorithm to transform the coordinates of mobile device 105 to the reference frame of device 108 coordinates and device 108 may then determine a distance from the mobile device 105 to device 108 by solving the equation: where D is distance from user to device 108, the user's position is identified by the three-dimensional coordinates x2, y2, and z2, and device 108's position is identified by the three-dimensional coordinates x1, y1, and z1. While the coordinates x, y, and z are used in the above equation, it should be recognized that any suitable coordinate system may be used; also see ¶063 - ¶065). Therefore, it would have been obvious for one of ordinary skill in the art at the time of filing the invention to combine Almalki’s method as outlined above with the concept of each of the first and second reference frames being a reference coordinate system, as taught by Agrawal for the purpose of implementing location estimations including multi-point/axes coordinates, such as x, y and z coordinates as the reference coordinate system.
Regarding claim 2, Almalki’ and Agrawal in combination teach the method of claim 1, and Almalki further teaches wherein the one or more estimate components include an orientation estimate (¶042; accelerometer and/or gyroscope may generate orientation data that specifies the orientation of the mobile device 100) and Agrawal further teaches wherein the one or more estimate components include a location estimate (¶063; estimation of “geographical location”). Therefore, it would have been obvious for one of ordinary skill in the art at the time of filing the invention to combine Almalki’s method with the concept wherein the one or more estimate components include a location estimate, as taught by Agrawal for the purpose of implementing more accurate location estimations.
Regarding claim 4, Almalki’ and Agrawal in combination teach the method of claim 1, and Almalki further teaches wherein the transformation includes one or more of a rotation transformation operation, a transformation operation, or a scale transformation operation (that include a translation transformation operation, (¶064, ¶066).
Regarding claim 5 (Currently Amended), Almalki’ and Agrawal in combination teach the method of claim 1, and Almalki further teaches the concept wherein a transformation includes one or more transformation operations that include includes a time shift operation that shifts time instances associated with an estimate component of the second estimate of position relative to time instances associated with a corresponding estimate component of the first estimate of position (¶062; the first sequence of images may be captured at a rate that depends on the relative speed of movement of the device user.. if motion data associated with mobile device indicates that device is moving at a speed exceeding a predefined threshold, the frequency of image capture by first camera may be increased accordingly or if speed of movement of mobile device is determined to fall below a predefined threshold, the rate of capture of images may be decreased).
Regarding claim 6, Almalki’ and Agrawal in combination teach the method of claim 1, and Almalki further teaches wherein the first motion estimator applies a first motion estimation technique and wherein the second motion estimator applies a second motion estimation technique different from the first motion estimation technique (See Fig 6).
Regarding claim 7, Almalki’ and Agrawal in combination teach the method of claim 1, and Almalki further teaches wherein the estimate of position formed by the first motion estimator is based on sensor data that is different from sensor data used by the second motion estimator (See Fig 6).
Regarding claim 9 (Original) Almalki’ and Agrawal in combination teach the method of claim 1, and Almalki further teaches comprising: switching (favoring) from the first motion estimator to the second motion estimator in response to at least one switching condition (¶076; a displacement indicated by motion sensor readings may be corrected by replacing values that do not match the image frame analysis values with the displacement estimated from image frame transformations. In particular, where one or more anomalies are detected in motion sensor readings, the estimated changes in position of the mobile device derived from an image frame analysis may be favored when calculating displacements and location of the device).
Regarding claim 10 (Original) Almalki’ and Agrawal in combination teach the method of claim 9, and Almalki further teaches wherein the switching (favoring) includes: applying the transformation to transform at least one estimate component of the one or more estimate components of the estimate of position formed by the second motion estimator from the reference frame associated with the second motion estimator to the reference frame associated with the first motion estimator (¶076; the estimated changes in position of the mobile device derived from an image frame analysis may be favored when calculating displacements and location of the device).
.
Regarding claim 11 (Original) Almalki’ and Agrawal in combination teach the method of claim 10, and Almalki further teaches wherein the at least two motion estimators (Fig 1; camera module 153 and motion sensor 182, per claim 1) include at least a third motion estimator (in an alternate embodiment: per ¶038; mobile device 100 may include a plurality of camera modules 153…may include both a front facing camera and a rear facing camera), the method further comprising:
determining a second transformation from the reference frame associated with the third motion estimator to the reference frame associated with the first motion estimator based at least in part on at least one estimate component of the one or more estimate components of the estimates of position formed by each of the first and third motion estimators (¶071; as was done for the first sequence of image frames captured by the front facing camera, for each pair of consecutive image frames in the second sequence, the mobile device identifies a transformation (e.g. a translation, a rotation, or a combination of one or more translations and rotations) between the image frames, in operation 314. In a similar manner as for the front facing camera, the mobile device may be calibrated to derive an estimate of the distance between the mobile device and the floor of the facility using the rear facing camera).
Almalki does not explicitly teach switching from the second motion estimator to the third motion estimator in response to at least one switching condition by applying the second transformation to transform at least one estimate component of the one or more estimate components of the estimate of position formed by the third motion estimator from the reference frame associated with the third motion estimator to the reference frame associated with the first motion estimator. However, as previously mentioned above, Almalki teaches the concept of switching (favoring) from one motion estimator to another motion estimator in response to at least one switching condition (¶076; a displacement indicated by motion sensor readings may be corrected by replacing values that do not match the image frame analysis values with the displacement estimated from image frame transformations. In particular, where one or more anomalies are detected in motion sensor readings, the estimated changes in position of the mobile device derived from an image frame analysis may be favored when calculating displacements and location of the device). Therefore, it would have been obvious for one of ordinary skill in the art at the time of filing the invention to try combining the two embodiments as outlined directly above with the same switching (favoring) technique put forth before in order for switching from the second motion estimator to the third motion estimator in response to at least one switching condition by applying the second transformation to transform at least one estimate component of the one or more estimate components of the estimate of position formed by the third motion estimator from the reference frame associated with the third motion estimator to the reference frame associated with the first motion estimator. . A person of ordinary skill in the art, upon reading the reference, would have recognized the desirability of such an improved method, as a person with ordinary skill would have good reason to pursue the known options within his or her technical grasp.
Regarding claim 12 (Original) Almalki’ and Agrawal in combination teach the method of claim 9, and Almalki further teaches wherein the at least one switching (favoring) condition is based on iv) an estimation uncertainty associated with the second motion estimator (¶076; where anomalies are detected in motion sensor readings, estimated changes in position of mobile device derived from image frame analysis may be favored when calculating displacements and location of the device).
Regarding claim 13 (Original), Almalki’ and Agrawal in combination teach the method of claim 1, and Almalki further teaches comprising: combining an estimate component of the one or more estimate components of the estimate of position formed by the first motion estimator with a corresponding estimate component of the one or more estimate components of the estimate of position formed by the second motion estimator, the combining based on:
i) the transformation (¶075; weighting the estimated change in position of the mobile device (attributable to image frames analysis, also see ¶080; weighting the first estimated direction and the second estimated direction), and
ii) a first set of weights associated with the estimate component formed by the first motion estimator and a second set of weights associated with the estimate component formed by the second motion estimator (¶075; and weighting the motion data associated with a pair of consecutive image frames (attributable to motion sensor readings; also see ¶080; weighting the first estimated direction and the second estimated direction). The motivation is the same as claim 11 above.
Regarding claim 14 (Original) Almalki’ and Agrawal in combination teach the method of claim 13, and Almalki teaches the concept where one or more anomalies are detected in motion sensor readings, the estimated changes in position of the mobile device derived from an image frame analysis may be favored when calculating displacements and location of the device (¶076), but Almalki is silent on wherein the weights in the first set of weights are a function of an estimation uncertainty associated with the estimate component formed by the first motion estimator, and wherein the weights in the second set of weights are a function of an estimation uncertainty associated with the estimate component formed by the second motion estimator. A person of ordinary skill in the art, upon reading the reference, would also have recognized the desirability of improved methods wherein the weights in the first set of weights are a function of an estimation uncertainty associated with the estimate component formed by the first motion estimator, and wherein the weights in the second set of weights are a function of an estimation uncertainty associated with the estimate component formed by the second motion estimator. Furthermore, the weighting due to an estimation of uncertainty associated with the estimate component formed by either estimator. would require no more than "ordinary skill" to choose upon. Therefore, it would have been obvious for one of ordinary skill in the art at the time of filing the invention to try having the weights in the first set of weights are a function of an estimation uncertainty associated with the estimate component formed by the first motion estimator, and wherein the weights in the second set of weights are a function of an estimation uncertainty associated with the estimate component formed by the second motion estimator, as a person with ordinary skill has good reason to pursue known options within his or her technical grasp.
Regarding claim 15 (Original) Almalki’ and Agrawal in combination teach the method of claim 13, but both are silent on the features of claim 15. A person of ordinary skill in the art, upon reading the reference, would also have recognized the desirability of improved methods wherein the weights in the first set of weights are inversely proportional to the covariance, the variance, or the standard deviation of the estimate component formed by the first motion estimator, and wherein the weights in the second set of weights are inversely proportional to the covariance, the variance, or the standard deviation of the estimate component formed by the second motion estimator. Furthermore, set of weights being inversely proportional to the covariance, the variance, or the standard deviation of the estimate component is one option in a finite number of solutions having set of weights are inversely proportional to the covariance, the variance, or the standard deviation of the estimate component. It would require no more than "ordinary skill" to choose one the option of being inverse or not inverse regarding proportional weighting. Therefore, it would have been obvious for one of ordinary skill in the art at the time of filing the invention to try having the weights in either set of being inversely proportional to the covariance, the variance, or the standard deviation of the estimate component formed by either motion estimator, as a person with ordinary skill has good reason to pursue known options within his or her technical grasp.
Regarding claim 16 (Original) Almalki’ and Agrawal in combination teach the method of claim 13, but both are silent on wherein the weights in the first set of weights and the weights in the second set of weights have fixed ratios between each other. A person of ordinary skill in the art, upon reading the reference, would also have recognized the desirability of improved methods wherein the weights in the first set of weights and the weights in the second set of weights have fixed ratios between each other. Furthermore, the weighting ratios were bound in a finite number of solutions having fixed ratios or not having fixed ratios between each other. It would require no more than "ordinary skill" to choose one of the two ratio options. Therefore, it would have been obvious for one of ordinary skill in the art at the time of filing the invention to try having weighting with fixed ratios between each other, as a person with ordinary skill has good reason to pursue known options within his or her technical grasp.
Regarding claim 17 (Previously Presented), Almalki teaches a system, comprising:
one or more sensors (camera module 153 & motion sensor 182) associated with a mobile device (mobile device 100) for generating sensor data from sensor measurements collected at the mobile device (¶025; see camera module 153, ¶029-¶038 and motion sensor 182, ¶039-¶042); and
a processing unit associated with the mobile device including at least one processor in communication with a memory (¶015; mobile device also includes a processor coupled to the memory and the first camera, the processing unit configured to:
receive sensor data from the one or more sensors (¶015; processor is configured to receive a first sequence of image frames captured by the first camera, where the first sequence of image frames is captured when the first camera is substantially faced toward a ceiling of the indoor facility. For each pair of consecutive image frames in the first sequence),
form, by employing a first motion estimator and a second motion estimator, respective first and second estimates of position of the mobile device over time based on the sensor data generated at the mobile device (¶025; see camera module 153, ¶029-¶038 and motion sensor 182, ¶039-¶042 , the first motion estimator having a first reference frame and the second motion estimator having a second reference frame (first & second pairs of image frames; ¶079-¶080), each of the first and second reference frames being a reference system, and each of the first and second estimates of position including one or more estimate components (¶039-¶042, ¶063-¶079, with Fig 6), and determine a transformation from the second reference frame to the first reference frame based at least in part on at least one estimate component of the one or more estimate components of the first and second estimates of position (processor is configured to identify a transformation between the pair of image frames and correlate the transformation with an estimated change in position of the mobile device. (¶015; processor further configured to obtain a first sequence of displacements based on the estimated changes in position of the mobile device for the pairs of consecutive image frames in the first sequence and determine the current location of the mobile device within the indoor facility based on an initial location of the mobile device and the first sequence of displacements, also see ¶080; direction of motion of the mobile device may then be determined in operation 610, based on at least one of the first estimated direction and the second estimated direction).
Almalki does not explicitly mention each of the first and second reference frames being a reference coordinate system. Agrawal teaches a system/method, comprising: forming, by a first motion estimator (¶063; a device 108 may determine whether the user/mobile device 105 has entered a geographical location that device 108 is located within … as “geographical location” refers to a building, geofence, or other boundary that identifies a point of interest, device 108 may use a range of GPS coordinates; see full details in (¶061 - ¶064 ) and a second motion estimator (¶063; device 108 may use coordinates based on another reference or measurement frame) included within, or that define a boundary of, the geographical location in which device 108 resides), respective first and second estimates of position of a mobile device over time based on sensor data generated at the mobile device (¶063 - ¶065), the first motiona reference coordinate system (GPS coordinates and coordinates based on another reference or measurement frame are of a reference coordinate system), and each of the first and second estimates of position including one or more estimate components (“geographical location” or one of the GPS coordinates from the range of the GPS coordinates), and determining a transformation from the second reference frame to the first reference frame based at least in part on at least one estimate component of the one or more estimate components of the first and second estimates of position (¶065; if device 108 coordinates were determined with respect to a different reference frame than the coordinates of mobile device 105, device 108 may execute a suitable transform algorithm to transform the coordinates of mobile device 105 to the reference frame of device 108 coordinates and device 108 may then determine a distance from the mobile device 105 to device 108 by solving the equation: where D is distance from user to device 108, the user's position is identified by the three-dimensional coordinates x2, y2, and z2, and device 108's position is identified by the three-dimensional coordinates x1, y1, and z1. While the coordinates x, y, and z are used in the above equation, it should be recognized that any suitable coordinate system may be used; also see ¶063 - ¶065). Therefore, it would have been obvious for one of ordinary skill in the art at the time of filing the invention to combine Almalki’s method as outlined above with the concept of each of the first and second reference frames being a reference coordinate system, as taught by Agrawal for the purpose of implementing location estimations including multi-point/axes coordinates, such as x, y and z coordinates as the reference coordinate system.
Regarding claim 18, Almalki’ and Agrawal in combination teach the system of claim 17, and Almalki further teaches the system comprising: an indoor positioning system (indoor navigation) associated with the mobile device configured to: receive a position estimate formed at least in part from each of the first and second estimates of position (¶075; the mobile device uses the motion sensor data in combination with the analysis of image frame transformations in obtaining the sequence of device displacements within the indoor facility. In at least some embodiments, each displacement in the sequence of displacements may be obtained by weighting the estimated change in position of the mobile device (attributable to image frames analysis) and the motion data associated with a pair of consecutive image frames (attributable to motion sensor readings), and
modify map data associated with an indoor environment in which the mobile device is located based at least in part on the received position estimate (¶048; indoor navigation application 126 may provide routing information during navigation, in real-time, in a graphical map interface, also see ¶047). The motivation is the same as claim 11 above.
Regarding claim 19 (Original), Almalki’ and Agrawal in combination teach the system of claim 17, and Almalki further teaches wherein the processing unit is further configured to: switch from the first motion estimator to the second motion estimator in response to at least one switching condition (¶076; a displacement indicated by motion sensor readings may be corrected by replacing values that do not match the image frame analysis values with the displacement estimated from image frame transformations. In particular, where one or more anomalies are detected in motion sensor readings, the estimated changes in position of the mobile device derived from an image frame analysis may be favored when calculating displacements and location of the device). The motivation is the same as claim 11 above.
Regarding claim 22, Almalki’ and Agrawal in combination teach the system of claim 17, and Almalki further teaches wherein the processing unit is further configured to: combine an estimate component of the estimate components of the first estimate of position with a corresponding estimate component of the one or more estimate components of the second estimate of position, the combining based on: i) the transformation (¶075; weighting the estimated change in position of the mobile device (attributable to image frames analysis, also see ¶080; weighting the first estimated direction and the second estimated direction), and
ii) a first set of weights associated with the estimate component formed by the and a second set of weights associated with the estimate component formed by the second estimate of position motion estimator (¶075; and weighting the motion data associated with a pair of consecutive image frames (attributable to motion sensor readings; also see ¶080; weighting the first estimated direction and the second estimated direction). The motivation is the same as claim 11 above.
Regarding claim 26 (Original), Almalki’ and Agrawal in combination teach the system of claim 17, and Agrawal further teaches wherein the processing unit is carried by the mobile device (Fig 3; processing unit(s) 310; also see; ¶052-¶054). Therefore, it would have been obvious for one of ordinary skill in the art at the time of filing the invention to combine Almalki’s system with the concept wherein the processing unit is carried by the mobile, as taught by Agrawal for the purpose of processing location estimations.
Regarding claim 27 (Original), Almalki’ and Agrawal in combination teach the system of claim 17, and Agrawal further teaches wherein one or more components of the processing unit is remotely located from the mobile device and is in network communication with the mobile device (Figs 1-3; ¶063; a device 108 may determine whether the user/mobile device 105 has entered a geographical location that device 108 is located within … as “geographical location” refers to a building, geofence, or other boundary that identifies a point of interest). Therefore, it would have been obvious for one of ordinary skill in the art at the time of filing the invention to combine Almalki’s system with the concept wherein one or more components of the processing unit is remotely located from the mobile device and is in network communication with the mobile device, as taught by Agrawal for the purpose of processing location estimations.
Regarding claim 35, Almalki’ and Agrawal in combination teach the method of claim 1, and Agrawal further teaches wherein the mobile device is located in an indoor environment (¶063; “geographical location” refers to a building, the method further comprising: generating new estimates of position by processing the second estimate of position (Figs 4 , calculating distances) the processing including applying the transformation to the second estimate of position (see claim 1); and by an indoor positioning system, processing the new estimates of position together with map data that is descriptive of the indoor environment to augment performance of the indoor positioning system (¶063; device 108 may use coordinates based on another reference or measurement frame) included within, or that define a boundary of, the geographical location in which device108 resides; also see ¶065 as also relevance as detailed in claim 1). Therefore, it would have been obvious for one of ordinary skill in the art at the time of filing the invention to combine Almalki’s method with the concept wherein one or more components of the processing unit is remotely located from the mobile device and is in network communication with the mobile device, as taught by Agrawal for the purpose of remotely processing location estimations.
Regarding claim 36, Almalki’ and Agrawal in combination teach the method, comprising:
forming, by a first motion estimator (camera module 153) and a second motion estimator (motion sensor 182), respective first and second trajectory estimates of position (¶016; trajectory of the mobile device within the indoor facility corresponding to the first sequence of images is then determined based on a sequence of the determined directions of motion for the pairs of consecutive image frames in the first sequence) of a mobile device (mobile device 100) over time based on sensor data generated at the mobile device (¶025; see camera module 153, ¶029-¶038 and motion sensor 182, ¶039-¶042), the first motion estimator having a first reference frame and the second motion estimator having a second reference frame, each of the first and second reference frames being a reference system (first & second pairs of image frames; ¶079-¶080), and each of the first and second trajectory estimates of position including one or more estimate components (¶039-¶042, ¶063-¶079, with Fig 6);
and determining a transformation from the second reference frame to the first reference frame based at least in part on at least one estimate component of the one or more estimate components of the first and second trajectory estimates of position (¶015; processor further configured to obtain a first sequence of displacements based on the estimated changes in position of the mobile device for the pairs of consecutive image frames in the first sequence and determine the current location of the mobile device within the indoor facility based on an initial location of the mobile device and the first sequence of displacements, also see ¶080; direction of motion of the mobile device may then be determined in operation 610, based on at least one of the first estimated direction and the second estimated direction.).
Almalki does not explicitly mention each of the first and second reference frames being a reference coordinate system. Agrawal teaches a system/method, comprising: forming, by a first motion estimator (¶063; a device 108 may determine whether the user/mobile device 105 has entered a geographical location that device 108 is located within … as “geographical location” refers to a building, geofence, or other boundary that identifies a point of interest, device 108 may use a range of GPS coordinates; see full details in (¶061 - ¶064 ) and a second motion estimator (¶063; device 108 may use coordinates based on another reference or measurement frame) included within, or that define a boundary of, the geographical location in which device 108 resides), respective first and second estimates of position of a mobile device over time based on sensor data generated at the mobile device (¶063 - ¶065), the first motiona reference coordinate system (GPS coordinates and coordinates based on another reference or measurement frame are of a reference coordinate system), and each of the first and second estimates of position including one or more estimate components (“geographical location” or one of the GPS coordinates from the range of the GPS coordinates), and determining a transformation from the second reference frame to the first reference frame based at least in part on at least one estimate component of the one or more estimate components of the first and second estimates of position (¶065; if device 108 coordinates were determined with respect to a different reference frame than the coordinates of mobile device 105, device 108 may execute a suitable transform algorithm to transform the coordinates of mobile device 105 to the reference frame of device 108 coordinates and device 108 may then determine a distance from the mobile device 105 to device 108 by solving the equation: where D is distance from user to device 108, the user's position is identified by the three-dimensional coordinates x2, y2, and z2, and device 108's position is identified by the three-dimensional coordinates x1, y1, and z1. While the coordinates x, y, and z are used in the above equation, it should be recognized that any suitable coordinate system may be used; also see ¶063 - ¶065). Therefore, it would have been obvious for one of ordinary skill in the art at the time of filing the invention to combine Almalki’s method as outlined above with the concept of each of the first and second reference frames being a reference coordinate system, as taught by Agrawal for the purpose of implementing trajectory estimates within a reference coordinate system.
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 MANCIL H LITTLEJOHN JR whose telephone number is (571)270-3718. The examiner can normally be reached M-F 8:30-5 (CST).
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/MANCIL LITTLEJOHN JR/Examiner, Art Unit 2685
/QUAN ZHEN WANG/Supervisory Patent Examiner, Art Unit 2685