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 .
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.
Claim(s) 1, 10, 19 and claims bellow are rejected under 35 U.S.C. 103 as being unpatentable over D1 US 20220137227 A1 in view of D01 Schacheter, Unification of automatic target tracking and automatic target recognition, Proc. of SPIE Vol. 9090, 909002 © 2014
Regarding claim 1, 10 D1 teaches
1. A device for detecting at least one object comprising a plurality of object segments in a monitored zone having - at least one FMCW LiDAR sensor for transmitting transmitted light beams into the monitored zone, for scanning a plurality of measurement points and for generating measurement data from transmitted light remitted or reflected by the measurement points, with the measurement data comprising radial speeds of the measurement points;[0042](fig. 2)
- a control and evaluation unit(130) for(intended use no patentable weight) evaluating the measurement data, with the control and evaluation unit being configured to segment the measurement points and to associate them at least in part with the object segments,[0048](clustering)
wherein the control and evaluation unit is further configured to determine a movement pattern of at least one of the object segments using the radial speeds of the measurement points associated with the object segments.[0040]
but does not teach
wherein the movement pattern comprises a relative movement of a first object segment with respect to a second object segment of the same object; and
determining said relative movement using spatially resolved radial speeds of measurement points associated with the first object segment and spatially resolved radial speeds of measurement points associated with the second object segment.
a control and evaluation unit for evaluating the measurement data, with the control and evaluation unit being configured to segment the measurement points and to associate them at least in part with the object segments, wherein the control and evaluation unit is further configured to determine a movement pattern of at least one of the object segments using the radial speeds of the measurement points associated with the object segments, and the movement pattern comprises a relative movement of a first object segment with respect to a second object segment of the same object;the control and evaluation unit configured to determine said relative movement using spatially resolved radial speeds of measurement points associated with the first object segment and spatially resolved radial speeds of measurement points associated with the second object segment; andthe control and evaluation unit configured to determine an azimuth angle p and a polar angle 6 from a time-discrete scanning of the measurement points and uses the determinations of the azimuth angle p and polar angle 0 to determine three-dimensional positions
D2 teaches
wherein the movement pattern comprises a relative movement of a first object segment with respect to a second object segment of the same object; and(page 5, 6 Track management Track grouping )
determining said relative movement using spatially resolved radial speeds of measurement points associated with the first object segment and spatially resolved radial speeds of measurement points associated with the second object segment. (page 5, 6 Track management Track grouping )
a control and evaluation unit for evaluating the measurement data, with the control and evaluation unit being configured to segment the measurement points and to associate them at least in part with the object segments, wherein the control and evaluation unit is further configured to determine a movement pattern of at least one of the object segments using the radial speeds of the measurement points associated with the object segments, and the movement pattern comprises a relative movement of a first object segment with respect to a second object segment of the same object;the control and evaluation unit configured to determine said relative movement using spatially resolved radial speeds of measurement points associated with the first object segment and spatially resolved radial speeds of measurement points associated with the second object segment; andthe control and evaluation unit configured to determine an azimuth angle p and a polar angle 6 from a time-discrete scanning of the measurement points and uses the determinations of the azimuth angle p and polar angle 0 to determine three-dimensional positions(page 5 and 6 page 3, 4 for velocity angle and position determination )
It will be obvious to one of ordinary skills in the art to modify teachings taught by D1 with teachings by D01 in order to group tracks into single convoy movement.
16. (new) The method in accordance with claim 11, further comprising: storing the determination of relative movement as a predetermined movement pattern(D06 implicit page 6), for(intended use no patentable weight ) detection in a teaching process; and using machine learning or artificial intelligence in combination with prior information to define feature spaces to classify persons or vehicles based on their radial speed and thus distinguish the persons or vehicles.
17. (new) The device in accordance with claim 1, wherein the device stores the determination of relative movement as a predetermined movement pattern(D01 implicit page 6 ), for(intended use no patentable weight) detection in a teaching process, for machine learning or artificial intelligence and uses the machine learning or artificial intelligence in combination with prior information to define feature spaces to classify persons or vehicles based on their radial speed and thus distinguish the persons or vehicles.
18. (new) The device in accordance with claim 1, wherein the determination of said relative movement using spatially resolved radial speeds of measurement points associated with the first object segment and spatially resolved radial speeds of measurement points associated with the second object segment takes place using the spatially resolved radial speed of the measurement points. (implicit page 5 and 6)
19. (new) A device for detecting at least one object comprising a plurality of object segments in a monitored zone, the device comprising:
at least one FMCW LiDAR sensor for transmitting transmitted light beams into the monitored zone, for scanning a plurality of measurement points and for generating measurement data from transmitted light remitted or reflected by the measurement points, with the measurement data comprising radial speeds of the measurement points;
a control and evaluation unit for evaluating the measurement data, with the control and evaluation unit being configured to segment the measurement points and to associate them at least in part with the object segments, wherein the control and evaluation unit is further configured to determine a movement pattern of at least one of the object segments using the radial speeds of the measurement points associated with the object segments, and the movement pattern comprises a relative movement of a first object segment with respect to a second object segment of the same object;the control and evaluation unit configured to determine said relative movement using spatially resolved radial speeds of measurement points associated with the first object segment and spatially resolved radial speeds of measurement points associated with the second object segment; andthe control and evaluation unit configured to determine an azimuth angle p and a polar angle 6 from a time-discrete scanning of the measurement points and uses the determinations of the azimuth angle p and polar angle 0 to determine three-dimensional positions
2, 11 The device in accordance with claim 1, wherein the control and evaluation unit is configured to segment the measurement points using the radial speeds and to associate them at least in part with the object segments.[0048]
3, 12 The device in accordance with claim 1, wherein the control and evaluation unit is configured to determine radial speeds of the objects and/or object segments and to extract features of the objects and/or object segments using the radial speeds of the objects and/or object segments.[0040-0041] [0048]
4, 13 The device in accordance with claim 3, wherein the control and evaluation unit is configured to classify the objects and/or object segments using the radial speeds of the objects and/or object segments. [0040-0041] [0048]
5, 14 The device in accordance with claim 1, wherein the control and evaluation unit is configured to filter the measurement points using the radial speed of the measurement points. [0040-0041] [0048](implicit clusters associated with each other by having similar radial velocities)
6, 15 The device in accordance with claim 5, wherein the control and evaluation unit is configured to discard measurement points having a radial speed below a predefined threshold value for the evaluation. [0040-0041] [0048](implicit if the object is moving with high radial velocity small radial velocity objects will not correspond to that object and would be discarded for that object)
7. The device in accordance with claim 1, wherein the FMCW LiDAR sensor is stationary.(fig. 3 everything depends on reference frame. For example if car is even moving and lidar is on the car, in the reference frame of the car the lidar is stationary)
9. The device in accordance with claim 1, wherein the device is configured to detect vehicles on a lane, with the control and evaluation device being configured to determine a rotation of wheels of the vehicle.[0023]
Claim(s) 8 is rejected under 35 U.S.C. 103 as being unpatentable over D1.
Although D1 does not explicitly teach
8. The device in accordance with claim 7, wherein the device has at least one further FMCW LiDAR sensor having a further monitored zone and the monitored zone at least partly overlaps the further monitored zone.
It is just simple multiplication of the parts in order to achieve large FOV without any gaps.
It would be obvious to one of ordinary skills in the art at the time of filing to modify teachings by D1 in order to achieve large FOV without any gaps
Response to Arguments
Applicant’s arguments with respect to claim(s) 07/01/2026 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
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/HOVHANNES BAGHDASARYAN/Examiner, Art Unit 3645
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