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 § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 30-49 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding Claims 31-35, 41-34, and 46-48, the limitation reciting “interpolated detector units” is indefinite because it is unclear whether the “interpolated detector units” refer to physical hardware components or virtual, mathematical constructs generated by software processing. If the “interpolated detector units” are purely virtual or algorithmic constructs, it is structurally unclear and indefinite how physical light acquisition can be performed “by” a non-physical virtual unit. Conversely, if they are intended to be physical hardware elements, the claims fail to recite their structural configuration or how they physically differ from the main detector array during operation, rending the physical scope of the claim ambiguous.
Regarding Claims 31, 37, 44, and 45, the limitation reciting “the plurality of interpolated detector units being in one-to-one correspondence with the plurality of calibrated detector units” is indefinite because the claims fail to define how this one-to-one relationship is maintained when detector subsets are reconfigured or shifted. Furthermore, this limitation creates an inconsistency and ambiguity when read in light of the specification, specifically Figs. 9-11), which illustrate mapping dynamics and spatial arrangements corresponding to an approximate two-to-one ratio rather than a one-to-one ratio. This discrepancy leaves one skilled in the art unable to determine the true boundaries and structural arrangement required to satisfy the “one-to-one correspondence” requirement.
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 30-31, 37, and 44-46 are rejected under 35 U.S.C. 103 as being unpatentable over Luo (WO 2021072752 A1) in view of Mati (US 2023/0031473 A1).
Regarding Claim 30, Luo teaches a detection method for a LiDAR ([P. 15, Para [0001]] The present invention provides a distance detection device, which can be used to measure the distance from a detection object to the detection device and the orientation of the detection object relative to the detection device. In one embodiment, the detection device may include radar, such as lidar), wherein the LiDAR comprises a plurality of light-emitter units ([P. 11, Para [0004]] The multiple laser diode chips opposite to the same optical element can be arranged at any suitable interval on the first surface of the substrate) and a plurality of calibrated detector units, the plurality of calibrated detector units being in one-to-one correspondence with the plurality of light-emitter units ([[P. 11, Para [0004]] Each light emitted from the light-transmitting area must correspond to each receiver one-to-one, that is, part of the laser light emitted by each laser diode chip is reflected by the object back to the corresponding receiver, so the emission and reception The positions of the laser diodes must be calibrated to make them correspond one-to-one), the detection method comprising:
performing a fixed value acquisition operation to determine fixed value acquisition data, wherein performing the fixed value acquisition operation comprises performing acquisition, by the plurality of light-emitter units and the plurality of calibrated detector units, to determine the fixed value acquisition data ([P. 13, Para. [0005]] The light emitting module 810 includes at least one laser diode package module in the first embodiment for emitting light signals, and the light signals emitted by the light emitting module 810 cover the FOV of the distance detection device 800; the reflected light receiving module 820 is used to receive the light emitted by the light emitting module 810 and reflect the light after encountering the object to be measured, and calculate the distance between the distance detecting device 800 and the object to be measured).
Luo is not relied upon as teaching that the detection method comprises: performing at least one interpolation acquisition operation to determine interpolation acquisition data; and determining a point cloud map based on the fixed value acquisition data and the interpolation acquisition data.
However, Mati teaches that the detection method comprises:
performing at least one interpolation acquisition operation to determine interpolation acquisition data ([Abstract] A computer-implemented method for generating a densified LiDAR point cloud includes receiving a plurality of LiDAR point clouds, including a reference LiDAR point cloud and remaining LiDAR point clouds, wherein the plurality of LiDAR point clouds is obtained based on measurements by a LiDAR device of a vehicle at subsequent measurement times); and
determining a point cloud map based on the fixed value acquisition data and the interpolation acquisition data ([Abstract] The densified LiDAR point cloud is generated by combining the reference LiDAR point cloud and the remaining LiDAR point clouds).
Luo and Mati are considered to be analogous to the claimed invention because they are both in the same field of optical distance measurement and LiDAR point cloud processing. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the detection method of Luo to include performing an interpolation acquisition operation to determine interpolation acquisition data and generating a densified point cloud map based on fixed and interpolation data as taught by Mati with a reasonable expectation of success. This modification would have been motivated by the desire to increase the spatial point density and resolution of the LiDAR point cloud map across sequential measurement cycles without requiring an increased physical pulse repetition rate or additional optical scanning hardware. By integrating Mati’s teaching of generating densified LiDAR point clouds from sequential measurement data into Luo’s distance detection system, the system can produce higher-resolution spatial maps for downstream object detection. A person of ordinary skill in the art would recognize that combining reference point cloud data with secondary interpolated measurement data would yield the predictable result of a denser, more accurate 3D point cloud map.
Regarding Claim 31, Luo teaches that performing the at least one interpolation acquisition operation comprises:
determining a plurality of interpolated detector units, the plurality of interpolated detector units being in one-to-one correspondence with the plurality of calibrated detector units ([P. 11, Para [0003]-[0004]] By arranging a plurality of the laser diode chips and the optical elements in the third and fourth directions, an M×N two-dimensional multi-line package is realized… each optical element is arranged opposite to the exit surface of six laser diode chips 303 arranged side by side, so that the emitted light of each laser diode chip 303 passes through the optical element After reflection, it is emitted through the light-transmitting area, wherein the number of laser diode chips 303 opposite to the same reflective surface can be reasonably selected according to the requirements of the actual device… the transmitting and receiving positions must be calibrated to make them correspond one-to-one).
Luo is not relied upon as teaching that performing the at least one interpolation acquisition operation comprises: performing acquisition, by the plurality of light-emitter units and the plurality of interpolated detector units, to determine the interpolation acquisition data.
However, Mati teaches that performing the at least one interpolation acquisition operation comprises:
performing acquisition, by the plurality of light-emitter units and the plurality of interpolated detector units, to determine the interpolation acquisition data ([Abstract] A computer-implemented method for generating a densified LiDAR point cloud includes receiving a plurality of LiDAR point clouds, including a reference LiDAR point cloud and remaining LiDAR point clouds, wherein the plurality of LiDAR point clouds is obtained based on measurements by a LiDAR device of a vehicle at subsequent measurement times).
Luo (as previously modified by Mati) and Mati are considered to be analogous to the claimed invention because they are both in the same field of optical distance measurement and LiDAR point cloud processing. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the detection system and method of Luo to include performing subsequent interpolation acquisition operations using designated emitter-detector groupings as taught by Mati with a reasonable expectation of success. This modification would have been motivated by the desire to increase spatial point density and point cloud resolution without adding hardware channels or optical elements. By integrating Mati’s teaching of obtaining point clouds based on measurements at subsequent measurement times into Luo’s detection method, the system can generate densified point cloud maps from sequential acquisition passes. A person of ordinary skill in the art would recognize that performing multi-time acquisitions across Luo’s calibrated 1-to-1 array structure would yield the predictable result of a higher-density LiDAR point cloud map.
Regarding Claim 37, Luo teaches that during performing the acquisition, by the plurality of light-emitter units and the plurality of calibrated detector units, to determine the fixed value acquisition data ([P. 13, Para. [0005]] The light emitting module 810 includes at least one laser diode package module in the first embodiment for emitting light signals, and the light signals emitted by the light emitting module 810 cover the FOV of the distance detection device 800; the reflected light receiving module 820 is used to receive the light emitted by the light emitting module 810 and reflect the light after encountering the object to be measured, and calculate the distance between the distance detecting device 800 and the object to be measured), the plurality of light-emitter units are calibrated light-emitter units ([P. 11, Para [0004]] the transmitting and receiving positions must be calibrated to make them correspond one-to-one), and
wherein performing the interpolation acquisition operation further comprises:
determining a plurality of interpolated light-emitter units based on the plurality of interpolated detector units, the plurality of interpolated light-emitter units being in one-to-one correspondence with the calibrated light-emitter units ([P. 11, Para [0003]-[0004]] By arranging a plurality of the laser diode chips and the optical elements in the third and fourth directions, an M×N two-dimensional multi-line package is realized… each optical element is arranged opposite to the exit surface of six laser diode chips 303 arranged side by side, so that the emitted light of each laser diode chip 303 passes through the optical element After reflection, it is emitted through the light-transmitting area, wherein the number of laser diode chips 303 opposite to the same reflective surface can be reasonably selected according to the requirements of the actual device… the transmitting and receiving positions must be calibrated to make them correspond one-to-one).
Luo is not relied upon as teaching that performing the interpolation acquisition operation further comprises: performing acquisition, by the plurality of interpolated light-emitter units and the plurality of interpolated detector units, to determine the interpolation acquisition data.
However, Mati teaches that performing the interpolation acquisition operation further comprises:
performing acquisition, by the plurality of interpolated light-emitter units and the plurality of interpolated detector units, to determine the interpolation acquisition data ([Abstract] A computer-implemented method for generating a densified LiDAR point cloud includes receiving a plurality of LiDAR point clouds, including a reference LiDAR point cloud and remaining LiDAR point clouds, wherein the plurality of LiDAR point clouds is obtained based on measurements by a LiDAR device of a vehicle at subsequent measurement times).
Luo (as previously modified by Mati) and Mati are considered to be analogous to the claimed invention because they are both in the same field of optical distance measurement and LiDAR point cloud processing. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the detection system and method of Luo to include performing subsequent interpolation acquisition operations using designated emitter-detector groupings as taught by Mati with a reasonable expectation of success. This modification would have been motivated by the desire to increase spatial point density and point cloud resolution without adding hardware channels or optical elements. By integrating Mati’s teaching of obtaining point clouds based on measurements at subsequent measurement times into Luo’s detection method, the system can generate densified point cloud maps from sequential acquisition passes. A person of ordinary skill in the art would recognize that performing multi-time acquisitions across Luo’s calibrated 1-to-1 array structure would yield the predictable result of a higher-density LiDAR point cloud map.
Regarding Claim 44, Luo teaches a LiDAR ([P. 15, Para [0001]] The present invention provides a distance detection device, which can be used to measure the distance from a detection object to the detection device and the orientation of the detection object relative to the detection device. In one embodiment, the detection device may include radar, such as lidar), comprising:
a plurality of light-emitter units ([P. 11, Para [0004]] The multiple laser diode chips opposite to the same optical element can be arranged at any suitable interval on the first surface of the substrate) and plurality of calibrated detector units, the plurality of calibrated detector units being in one-to-one correspondence with the plurality of light-emitter units ([[P. 11, Para [0004]] Each light emitted from the light-transmitting area must correspond to each receiver one-to-one, that is, part of the laser light emitted by each laser diode chip is reflected by the object back to the corresponding receiver, so the emission and reception The positions of the laser diodes must be calibrated to make them correspond one-to-one); and
a detection processor device configured to:
perform a fixed value acquisition operation to determine fixed value acquisition data by performing acquisition, by the plurality of light-emitter units and the plurality of calibrated detector units, to determine the fixed value acquisition data ([P. 13, Para. [0005]] The light emitting module 810 includes at least one laser diode package module in the first embodiment for emitting light signals, and the light signals emitted by the light emitting module 810 cover the FOV of the distance detection device 800; the reflected light receiving module 820 is used to receive the light emitted by the light emitting module 810 and reflect the light after encountering the object to be measured, and calculate the distance between the distance detecting device 800 and the object to be measured).
Luo is not relied upon as teaching that the device is configured to perform at least one interpolation acquisition operation to determine interpolation acquisition data; and determine a point cloud map based on the fixed value acquisition data and the interpolation acquisition data.
However, Mati teaches that the device is configured to perform at least one interpolation acquisition operation to determine interpolation acquisition data ([Abstract] A computer-implemented method for generating a densified LiDAR point cloud includes receiving a plurality of LiDAR point clouds, including a reference LiDAR point cloud and remaining LiDAR point clouds, wherein the plurality of LiDAR point clouds is obtained based on measurements by a LiDAR device of a vehicle at subsequent measurement times); and
determine a point cloud map based on the fixed value acquisition data and the interpolation acquisition data ([Abstract] The densified LiDAR point cloud is generated by combining the reference LiDAR point cloud and the remaining LiDAR point clouds).
Luo and Mati are considered to be analogous to the claimed invention because they are both in the same field of optical distance measurement and LiDAR point cloud processing. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the device of Luo to include performing an interpolation acquisition operation to determine interpolation acquisition data and generating a densified point cloud map based on fixed and interpolation data as taught by Mati with a reasonable expectation of success. This modification would have been motivated by the desire to increase the spatial point density and resolution of the LiDAR point cloud map across sequential measurement cycles without requiring an increased physical pulse repetition rate or additional optical scanning hardware. By integrating Mati’s teaching of generating densified LiDAR point clouds from sequential measurement data into Luo’s distance detection system, the system can produce higher-resolution spatial maps for downstream object detection. A person of ordinary skill in the art would recognize that combining reference point cloud data with secondary interpolated measurement data would yield the predictable result of a denser, more accurate 3D point cloud map.
Regarding Claim 45, Luo teaches a LiDAR ([P. 15, Para [0001]] The present invention provides a distance detection device, which can be used to measure the distance from a detection object to the detection device and the orientation of the detection object relative to the detection device. In one embodiment, the detection device may include radar, such as lidar), comprising:
a plurality of light-emitter units ([P. 11, Para [0004]] The multiple laser diode chips opposite to the same optical element can be arranged at any suitable interval on the first surface of the substrate) and plurality of calibrated detector units, the plurality of calibrated detector units being in one-to-one correspondence with the plurality of light-emitter units ([[P. 11, Para [0004]] Each light emitted from the light-transmitting area must correspond to each receiver one-to-one, that is, part of the laser light emitted by each laser diode chip is reflected by the object back to the corresponding receiver, so the emission and reception The positions of the laser diodes must be calibrated to make them correspond one-to-one);
an acquisition module configured to:
perform a fixed value acquisition operation to determine fixed value acquisition data by performing acquisition, by the plurality of light-emitter units and the plurality of calibrated detector units, to determine the fixed value acquisition data ([P. 13, Para. [0005]] The light emitting module 810 includes at least one laser diode package module in the first embodiment for emitting light signals, and the light signals emitted by the light emitting module 810 cover the FOV of the distance detection device 800; the reflected light receiving module 820 is used to receive the light emitted by the light emitting module 810 and reflect the light after encountering the object to be measured, and calculate the distance between the distance detecting device 800 and the object to be measured).
Luo is not relied upon as teaching that the device is configured to perform at least one interpolation acquisition operation to determine interpolation acquisition data; and determine a point cloud map based on the fixed value acquisition data and the interpolation acquisition data.
However, Mati teaches that the device is configured to perform at least one interpolation acquisition operation to determine interpolation acquisition data ([Abstract] A computer-implemented method for generating a densified LiDAR point cloud includes receiving a plurality of LiDAR point clouds, including a reference LiDAR point cloud and remaining LiDAR point clouds, wherein the plurality of LiDAR point clouds is obtained based on measurements by a LiDAR device of a vehicle at subsequent measurement times); and
determine a point cloud map based on the fixed value acquisition data and the interpolation acquisition data ([Abstract] The densified LiDAR point cloud is generated by combining the reference LiDAR point cloud and the remaining LiDAR point clouds).
Luo and Mati are considered to be analogous to the claimed invention because they are both in the same field of optical distance measurement and LiDAR point cloud processing. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the device of Luo to include performing an interpolation acquisition operation to determine interpolation acquisition data and generating a densified point cloud map based on fixed and interpolation data as taught by Mati with a reasonable expectation of success. This modification would have been motivated by the desire to increase the spatial point density and resolution of the LiDAR point cloud map across sequential measurement cycles without requiring an increased physical pulse repetition rate or additional optical scanning hardware. By integrating Mati’s teaching of generating densified LiDAR point clouds from sequential measurement data into Luo’s distance detection system, the system can produce higher-resolution spatial maps for downstream object detection. A person of ordinary skill in the art would recognize that combining reference point cloud data with secondary interpolated measurement data would yield the predictable result of a denser, more accurate 3D point cloud map.
Regarding Claim 46, Luo teaches that the acquisition module ([P. 15, Para [0001]] The present invention provides a distance detection device, which can be used to measure the distance from a detection object to the detection device and the orientation of the detection object relative to the detection device. In one embodiment, the detection device may include radar, such as lidar) comprises: a fixed value acquisition unit,
wherein the fixed value acquisition unit is configured to perform the fixed value acquisition operation, and the interpolation acquisition unit is configured to perform the interpolation acquisition operation ([P. 13, Para. [0005]] The light emitting module 810 includes at least one laser diode package module in the first embodiment for emitting light signals, and the light signals emitted by the light emitting module 810 cover the FOV of the distance detection device 800; the reflected light receiving module 820 is used to receive the light emitted by the light emitting module 810 and reflect the light after encountering the object to be measured, and calculate the distance between the distance detecting device 800 and the object to be measured).
Luo is not relied upon as teaching that the acquisition module comprises an interpolation acquisition unit, wherein the interpolation acquisition unit comprises: a detector selector and a processor, wherein the detector selector is configured to determine a plurality of interpolated detector units, the plurality of interpolated detector units being in one-to-one correspondence with the plurality of calibrated detector units, and wherein the processor is configured to perform acquisition, by the plurality of light-emitter units and the plurality of interpolated detector units, to determine the interpolation acquisition data.
However, Mati teaches that the acquisition module comprises an interpolation acquisition unit, wherein the interpolation acquisition unit comprises: a detector selector and a processor, wherein the detector selector is configured to determine a plurality of interpolated detector units, the plurality of interpolated detector units being in one-to-one correspondence with the plurality of calibrated detector units, and wherein the processor is configured to perform acquisition, by the plurality of light-emitter units and the plurality of interpolated detector units, to determine the interpolation acquisition data ([Abstract] A computer-implemented method for generating a densified LiDAR point cloud includes receiving a plurality of LiDAR point clouds, including a reference LiDAR point cloud and remaining LiDAR point clouds, wherein the plurality of LiDAR point clouds is obtained based on measurements by a LiDAR device of a vehicle at subsequent measurement times… The densified LiDAR point cloud is generated by combining the reference LiDAR point cloud and the remaining LiDAR point clouds).
Luo and Mati are considered to be analogous to the claimed invention because they are both in the same field of optical distance measurement and LiDAR point cloud processing. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the device of Luo to include an interpolation acquisition unit comprising a detector selector and processor configured to perform interpolation acquisition operations using interpolated detector units mapped in 1-to-1 correspondence with Luo’s calibrated detector units as taught by Mati with a reasonable expectation of success. This modification would have been motivated by the desire to increase spatial point density and point cloud resolution without adding hardware channels or optical elements. By applying Mati’s time-sequential interpolation of Luo’s calibrated 1-to-1 array layout, configuring the interpolated detector units to correspond 1-to-1 with the calibrated physical units preserves spatial alignment and grid symmetry during point cloud densification. A person of ordinary skill in the art would recognize that partitioning the system into dedicated functional units (a fixed value acquisition unit and an interpolation acquisition unit comprising a detector selector and processor) yields the predictable result of a denser, more accurate 3D point cloud map.
Allowable Subject Matter
Claims 32-36, 38-43, and 47-49 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter:
Claim 32: “partially different” detector subset logic
Claims 33-36: by virtue of dependence on Claim 32
Claim 38: “partially different” emitter subset logic
Claim 39: by virtue of dependence on Claim 38
Claim 40: “determining a second detection angle, the interpolation acquisition data corresponding to the second detection angle”
Claims 41-43: by virtue of dependence on Claim 40
Claim 47: “partially different” detector subset logic
Claim 48: “partially different” emitter subset logic
Claim 49: “determining a second detection angle, the interpolation acquisition data corresponding to the second detection angle”
Conclusion
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/E.H.H./Patent Examiner, Art Unit 3645
/JAMES R HULKA/Primary Examiner, Art Unit 3645
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