DETAILED ACTION
The action is in response to the original filing on July 23, 2024 and the Remarks and Amendments filed on April 9, 2026. Claims 1-20 are pending and have been considered below. Claims 1, 2, 4-6, 9-14, and 16-19 are amended accordingly.
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
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, 3, 4, 6, 7, & 10 are rejected under 35 U.S.C. 103 as being unpatentable over Benny Eliyahu (Pat. Pub. WO-2024075121-A1, herein after “Benny”) in view of Kurt Konolige (Pat. Pub. US-20160288330-A1, herein after “Konolige”).
Regarding claim 1, Benny teaches [a] method for producing three-dimensional spectral models of a production system, the method comprising:
receiving input data (Benny, Page 25, “Multi-spectral images”) from a plurality of spectral markers (Benny, Page 25, “Targets”) disposed in the production system (Benny, Page 26, Agricultural setting or other relevant use case) “System 100 uses multi- spectral sensor 104 to generate the spectral data cube of the given observed area, to investigate and analyze the suspected potential targets using additional sensors and to identify potential targets within the spectral data cube all during the flight over the area, with no need to download the captured material for analysis in a ground station. This is achieved by system's 100 real-time analysis of the spectral data cube together with the input data coming from the additional sensors to better detect and identify the potential targets” (Benny, Page 25) in which “[a] non-limiting example is a real-time multi-spectral system 100 that is used in an agriculture setting. In this setting the target spectral signature can be of a given agriculture product that system 100 is trying to identify and further investigate” (Benny, Page 26);
generating the plurality of spectral markers (Benny, Page 6 “Targets”) within a three-dimensional space (Benny, Page 6, “Multi-spectral data cube”) based upon the input data “generate a multi-spectral data cube of a second FOV viewed by the multi- spectral sensor, utilizing the multi- spectral sensor, the calculated exposure times and the atmospheric correction matrix, wherein the generation of the multi- spectral data cube includes radiometric calibration and multi-channel registration; identify, utilizing the multi- spectral data cube, one or more potential targets, wherein each target is group of pixels identified within the multi-spectral data cube with a spectral signature that corresponds to at least one of the obtained target spectral signatures” (Benny, Page 6);
reading each of the spectral markers (Benny, Page 36, “Targets”) within the three-dimensional space to determine a unique spectral signature (Benny, Page 36, “Reflective spectral signature”) corresponding to and emitted from each of the spectral markers “multi- spectral system 100 can be configured to obtain: (A) a machine learning model capable of receiving the image of the scene and identify the existence of at least one object of the automatically identified objects within the scene, each identified object is associated with: (i) a location within the scene, and (ii) a predetermined representative reflective spectral signature, and (B) the image of the scene (block 1002)” (Benny, page 36) where each of the targets may be different materials at different positions within the 3D space, and appear a unique color depending on the respective material, and each spectral signature is emitted from the corresponding material in order to be detected;
associating each unique spectral signature of each of the spectral markers with a unique identification to generate a plurality of unique identifications, wherein each unique identification corresponds to a location within the three-dimensional space “multi- spectral system 100 can be configured to obtain: (A) a machine learning model capable of receiving the image of the scene and identify the existence of at least one object of the automatically identified objects within the scene, each identified object is associated with: (i) a location within the scene, and (ii) a predetermined representative reflective spectral signature, and (B) the image of the scene (block 1002)” (Benny, Page 36) where the spectral signal is identified by its reflective color or location or a combination, and each signal having its own location can be considered unique;
providing the plurality of unique identifications (Benny, Page 36, “Reflective spectral signature” and “location within the scene”)to a robot (Benny, Page 25, “Observation pod”) within the three-dimensional space, wherein the robot positions itself during an inspection of the production system by the robot within the three-dimensional space according to the locations within the three-dimensional space corresponding to the plurality of unique identifications “In accordance with the presently disclosed subject matter, the real-time multi- spectral system 100 can be optionally enclosed within an observation pod” (Benny, Page 25) where the observation pod may be attached to another device or location. Additionally, “System 100 is capable of keeping observation capabilities on a given observed area by controlling the movement of the multi-spectral sensor's 104 lens and of the lenses of the additional sensors (e.g., the wide daylight sensor 106, the narrow daylight sensor 110, the wide thermal sensor 114, the narrow thermal sensor 118, the narrow SWIR sensor 108, the laser rangefinder 116, the laser pointer 112, etc.) while the platform is in motion. In many cases the various sensors in pod or pay load, although they might have different FOVs, the center FOV of each sensor is aligned to the same direction, enabling the system to use different sensors for the same target location” (Benny, Page 25); and
reconstructing a three-dimensional spectral model including the locations “System 100 can utilize the atmospheric simulator to generate more than one un-calibrated multi-spectral data cube with known target material from a single given calibrated multi-spectral data cube using different atmospheric conditions, thus allowing to easily create a large training data set from a small number of calibrated multi-spectral data cubes which are labeled with known target materials and their location within the scene” (Benny, Page 18) where the model may be labeled with their material and location.
Benny does not explicitly teach wherein the robot positions itself during an inspection of the production system by the robot within the three-dimensional space according to the locations within the three-dimensional space corresponding to the plurality of unique identifications.
Konolige teaches wherein the robot positions itself during an inspection of the production system by the robot within the three-dimensional space according to the locations within the three-dimensional space corresponding to the plurality of unique identifications “a virtual environment may be built up using a 3D volumetric or surface model to integrate information (e.g., from different sensors). This may allow the system to operate within a larger environment, such as in cases where one sensor may be insufficient to cover a large environment. Such techniques may also increase the level of detail captured, which may help the robotic device perform various tasks” (Konolige, ¶ [0066]) additionally, “The robotic arm may be configured to move through the scene as multiple views of the calibration pattern on the robotic arm are collected” (Konolige, ¶ [0080]). It is known in the art to have robots capable of navigating a scanned environment to perform tasks.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of producing 3-dimensional spectral models taught by Benny with the use of a robot capable to move about its 3-dimensional space taught by Konolige to produce a spectral observing robot capable of moving about the 3-dimentional space. The motivation to do so would be to observe more than what is immediately in the camera’s line of sight, or to see around object that are in the way.
Regarding claim 3, Benny in view of Konolige teach [t]he method of Claim 1, further comprising performing an action in response to the three-dimensional spectral model “System 100 is capable of keeping observation capabilities on a given observed area by controlling the movement of the multi-spectral sensor's 104 lens and of the lenses of the additional sensors (e.g., the wide daylight sensor 106, the narrow daylight sensor 110, the wide thermal sensor 114, the narrow thermal sensor 118, the narrow SWIR sensor 108, the laser rangefinder 116, the laser pointer 112, etc.) while the platform is in motion. In many cases the various sensors in pod or pay load, although they might have different FOVs, the center FOV of each sensor is aligned to the same direction, enabling the system to use different sensors for the same target location” (Benny, Page 25), the 3D model may also be “used for rendering game scenes by a game engine” (Benny, Page 22).
Regarding claim 4, Benny in view of Konolige teach [t]he method of Claim 1, wherein reading each of the spectral markers within the three-dimensional space (Page 26, “Spectral data cube”) to determine the unique spectral signature corresponding to each of the spectral markers comprises:
reading a pattern (Benny, Page 26, “unique reflection”) of spectral values (Benny, Page 26, “Invisible wavelength”) that is unique to each of the spectral markers (Benny, Page 26, “Target”) “Another example is of system 100 trying to identify special leaves (e.g., of artificial material) that are visually similar to all other leaves but are different in some invisible wavelength in which these special leaves have unique reflection which differs from regular leaves. In some cases, system 100 is not provided with specific target spectral signatures. In these cases, system 100 can determine if one or more anomalies exist in the spectral data cube of the given scene” (Benny, Page 26) where a pattern or unique invisible wavelength can be read from the target within the three-dimensional space.
Regarding claim 6, Benny in view of Konolige teach [t]he method of Claim 1, further comprising varying the unique spectral signature of at least one of the spectral markers over a period of time “The filter wheel is used to rotatably position a filter with a given wavelength range in the imaging path of the sensor to capture an image in that wavelength range. The filter in the imaging path of the sensor at a given time- window and/or interval of time is the active filter at that time window” (Benny, Page 16), wherein varying the unique spectral signature comprises:
cyclically or non-cyclically varying the unique spectral signature that is emitted “Multi- spectral sensor 104 can alternatively comprise two or more filter wheels, which can be used to combine different filters from each of the filter wheels simultaneously. In addition, multi- spectral sensor 104 can alternatively utilize one or more of the following filter methods: (a) a Fabry-Perot interferometer (FPI), (b) a Linear Variable filter (LVF), and (c) a circular variable filter. Multi- spectral sensor 104 can be alternatively comprised of multiple sensors, each sensor captures images of the scene at a different wavelength range, or a combination of multiple sensors with filters enabling each sensor to capture different wavelength ranges” (Benny, Page 16) where using a different filter or method of reading the target is considered varying the observed spectral signature;
varying a wave amplitude or a frequency of the at least one of the spectral markers “In this setting the target spectral signature can be of a given agriculture product that system 100 is trying to identify and further investigate. For example, a spectral signature of a strawberry. The spectral signature of the strawberry is a vector associated with multiple values. Each value in this vector is associated with the spectral variation of reflectance or emittance of a strawberry in the wavelength ranges that can be captured by the multi-spectral sensor 104” (Benny, Page 26) where over a period of time spectral signatures of agricultural products can be changed and observed, additionally “The filter wheel is used to rotatably position a filter with a given wavelength range in the imaging path of the sensor to capture an image in that wavelength range. The filter in the imaging path of the sensor at a given time- window and/or interval of time is the active filter at that time window. The wheel is then turned to position the next filter, which has a different wavelength range in the imaging path of the sensor allowing the sensor to capture an image in the different wavelength range. Rotating the filter wheel allows the multi- spectral sensor 104 to capture a series of images in multiple wavelength ranges over a given time-frame.” (Benny, Page 16).
Regarding claim 7, Benny in view of Konolige teach [t]he method of Claim 1, further comprising transmitting a supplemental data signal (Benny, Page 25 “thermal sensor” information) from at least one of the spectral markers “System 100 is capable of keeping observation capabilities on a given observed area by controlling the movement of the multi-spectral sensor's 104 lens and of the lenses of the additional sensors (e.g., the wide daylight sensor 106, the narrow daylight sensor 110, the wide thermal sensor 114, the narrow thermal sensor 118, the narrow SWIR sensor 108, the laser rangefinder 116, the laser pointer 112, etc.) while the platform is in motion. In many cases the various sensors in pod or pay load, although they might have different FOVs, the center FOV of each sensor is aligned to the same direction, enabling the system to use different sensors for the same target location” (Benny, Page 25) where the thermal sensor receives information about temperature, wherein the supplemental data signal is comprised of at least one signal received from the production system “This is achieved by system's 100 real-time analysis of the spectral data cube together with the input data coming from the additional sensors to better detect and identify the potential targets” (Benny, Page 25).
Regarding claim 10, Benny in view of Konolige teach [t]he method of Claim 1, wherein reading each of the spectral markers within the three-dimensional space to determine the unique spectral signature corresponding to each one of the spectral markers comprises reading the spectral markers with a spectral device configured to read a pattern (Benny, Page 26, “unique reflection”) of spectral values that is unique to each of the spectral markers, wherein the spectral device is disposed on the robot “In accordance with the presently disclosed subject matter, the real-time multi- spectral system 100 can be optionally enclosed within an observation pod. The observation pod can be used as a stand-alone system and/or can be installed as a special purpose payload on a platform, for example: on a personal platform, on a watch tower as part of a wider border defense system, on a ground vehicle, on an aerial platform, in space, etc. When system 100 is installed in an observation pod on an aerial platform, it can detect potential targets in a given scene in real-time, without the need to download information from the aerial platform to a ground station for human operator analysis. System 100 is capable of keeping observation capabilities on a given observed area by controlling the movement of the multi-spectral sensor's 104 lens and of the lenses of the additional sensors (e.g., the wide daylight sensor 106, the narrow daylight sensor 110, the wide thermal sensor 114, the narrow thermal sensor 118, the narrow SWIR sensor 108, the laser rangefinder 116, the laser pointer 112, etc.) while the platform is in motion.” (Benny, Page 25) where system 100 can detect new or predetermined patterns of spectral values using the various sensors disposed on the robot which could be a vehicle or other tool, and the emitted spectral value can be unique as different materials emit different spectral outputs as disclosed previously in the invention (Benny, Pages 26 & 36).
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Benny in view of Konolige, and further in view of Mark Profio (Pat. Pub. US-20110295113, herein after “Profio”).
Regarding claim 2, Benny in view of Konolige teach [t]he method of Claim 1.
Benny in view of Konolige does not explicitly teach displaying the three-dimensional spectral model.
Profio teaches displaying the three-dimensional spectral model “Thereafter, at 86, three-dimensional (3D) volume visualization is performed on the 2D stacks of images to form 3D volume visualization models. In particular, maximum intensity pixel projection is performed through each stack of 2D images resulting in a 3D MIP volume at each point in time.” (Profio, ¶ [027]) where taking 2D splices of an object using x-ray methods, then combining them produces a 3D model.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of producing 3-dimensional spectral models taught by Benny with the display of volume taught by Profio to produce a 3-dimensional spectral model display. The motivation to do so would be to visualize the model.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Benny in view of Karl Garsha (Pat. Pub. JP-2021047207-A, herein after “Garsha”).
Regarding claim 9, Benny in view of Konolige teaches [t]he method of Claim 1.
Benny in view of Konolige fails to teach further comprising maintaining at least a portion of each of the spectral markers at an invariant spectral value, wherein maintaining the at least a portion of each of the spectral markers at an invariant spectral value comprises powering the at least a portion of each of the spectral markers from a power source within the three-dimensional space or from an outside or independent power source.
Garsha teaches further comprising maintaining at least a portion of each of the spectral markers at an invariant spectral value, wherein maintaining the at least a portion of each of the spectral markers at an invariant spectral value comprises powering the at least a portion of each of the spectral markers from a power source within the three-dimensional space or from an outside or independent power source “The power and temperature of the spectrum source 410 may be stabilized and monitored by closed-loop electronics and / or multi-bandpass filters 410a. The multi-bandpass filter 410a has n predetermined passbands and is positioned in front of the spectrum source 410. In an example embodiment of the invention, a spectrum acquisition system 422, eg, a microscope-based light acquisition device, includes or is coupled to a spectrum camera 443. The spectrum acquisition device 442 includes a scanning platform 445” (Garsha, Page 11) where maintaining a stable power of the spectrum source outputs a maintained spectrum.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of producing 3-dimensional spectral models taught by Benny with the use of maintaining a constant spectral source taught by Garsha to produce a reference spectral output. The motivation to do so would be to compare the constant spectral output with other spectral signatures to identify differences.
Claims 11, 12, & 14 are rejected under 35 U.S.C. 103 as being unpatentable over Benny in view of Konolige, Profio, and further in view of Garsha.
Regarding claim 11, Benny teaches [a] computing system, comprising:
one or more processors “Multi- spectral system 100 further comprises processing circuitry 102” (Benny, Page 24);
a plurality of spectral markers communicated to the one or more processors, wherein the plurality of spectral markers are disposed in a production system “The capture can be for example during a flight of a platform to which multi-spectral sensor 104 is attached. A frame is captured per wavelength of the sensor. Each frame has a different angle towards the scene and targets within the scene due to the movement of the platform over the scene while capturing the frames” (Benny, Page 22);
a robot communicated to the one or more processors, wherein the robot is configured to read the plurality of spectral markers “The observation pod can be used as a stand-alone system and/or can be installed as a special purpose payload on a platform, for example: on a personal platform, on a watch tower as part of a wider border defense system, on a ground vehicle, on an aerial platform, in space, etc. When system 100 is installed in an observation pod on an aerial platform, it can detect potential targets in a given scene in real-time, without the need to download information from the aerial platform to a ground station for human operator analysis” (Benny, Page 25);
at least one sensor communicated to the one or more processors “System 100 is capable of keeping observation capabilities on a given observed area by controlling the movement of the multi-spectral sensor's 104 lens and of the lenses of the additional sensors (e.g., the wide daylight sensor 106, the narrow daylight sensor 110, the wide thermal sensor 114, the narrow thermal sensor 118, the narrow SWIR sensor 108, the laser rangefinder 116, the laser pointer 112, etc.) while the platform is in motion” (Benny, Page 25); and
a memory system comprising one or more non-transitory computer-readable media storing instructions that, when executed by at least one of the one or more processors, cause the computing system to perform operations, the operations comprising “The processing circuitry 102 can read the relevant parameters of each algorithm from a first designated memory area of system 100, read the spectral data cube, preform the algorithms on the spectral data cube's images and save the results in a second designated memory area of system 100” (Benny, Page 28):
receiving input data from the plurality of spectral markers, the input data representing the production system “System 100 uses multi- spectral sensor 104 to generate the spectral data cube of the given observed area, to investigate and analyze the suspected potential targets using additional sensors and to identify potential targets within the spectral data cube all during the flight over the area, with no need to download the captured material for analysis in a ground station. This is achieved by system's 100 real-time analysis of the spectral data cube together with the input data coming from the additional sensors to better detect and identify the potential targets” (Benny, Page 25) in which “[a] non-limiting example is a real-time multi-spectral system 100 that is used in an agriculture setting. In this setting the target spectral signature can be of a given agriculture product that system 100 is trying to identify and further investigate” (Benny, Page 26);
generating the plurality of spectral markers within a three-dimensional space based upon the input data “generate a multi-spectral data cube of a second FOV viewed by the multi- spectral sensor, utilizing the multi- spectral sensor, the calculated exposure times and the atmospheric correction matrix, wherein the generation of the multi- spectral data cube includes radiometric calibration and multi-channel registration; identify, utilizing the multi- spectral data cube, one or more potential targets, wherein each target is group of pixels identified within the multi-spectral data cube with a spectral signature that corresponds to at least one of the obtained target spectral signatures” (Benny, Page 6);
reading each of the spectral markers within the three-dimensional space to determine a unique spectral signature corresponding to and emitted from each of the spectral markers, wherein reading the plurality of spectral markers comprises reading the spectral markers with a spectral device configured to read a pattern of spectral values that is unique to of each of the spectral markers, and wherein the spectral device is disposed on the robot “In accordance with the presently disclosed subject matter, the real-time multi- spectral system 100 can be optionally enclosed within an observation pod. The observation pod can be used as a stand-alone system and/or can be installed as a special purpose payload on a platform, for example: on a personal platform, on a watch tower as part of a wider border defense system, on a ground vehicle, on an aerial platform, in space, etc. When system 100 is installed in an observation pod on an aerial platform, it can detect potential targets in a given scene in real-time, without the need to download information from the aerial platform to a ground station for human operator analysis. System 100 is capable of keeping observation capabilities on a given observed area by controlling the movement of the multi-spectral sensor's 104 lens and of the lenses of the additional sensors (e.g., the wide daylight sensor 106, the narrow daylight sensor 110, the wide thermal sensor 114, the narrow thermal sensor 118, the narrow SWIR sensor 108, the laser rangefinder 116, the laser pointer 112, etc.) while the platform is in motion.” (Benny, Page 25) where system 100 can detect new or predetermined patterns of spectral values using the various sensors disposed on the robot which could be a vehicle or other tool;
associating each unique spectral signature of each of the spectral markers with a unique identification to generate a plurality of unique identifications, wherein each unique identification corresponds to a location within the three-dimensional space “multi- spectral system 100 can be configured to obtain: (A) a machine learning model capable of receiving the image of the scene and identify the existence of at least one object of the automatically identified objects within the scene, each identified object is associated with: (i) a location within the scene, and (ii) a predetermined representative reflective spectral signature, and (B) the image of the scene (block 1002)” (Benny, Page 36) where the spectral signal is identified by its reflective color or location or a combination;
providing the plurality of unique identifications to the robot within the three-dimensional space, wherein the robot positions itself during an inspection of the production system by the robot within the three-dimensional space according to the locations within the three-dimensional space corresponding to the plurality of unique identifications “In accordance with the presently disclosed subject matter, the real-time multi- spectral system 100 can be optionally enclosed within an observation pod” (Benny, Page 25) where the observation pod may be attached to another device or location. Additionally, “System 100 is capable of keeping observation capabilities on a given observed area by controlling the movement of the multi-spectral sensor's 104 lens and of the lenses of the additional sensors (e.g., the wide daylight sensor 106, the narrow daylight sensor 110, the wide thermal sensor 114, the narrow thermal sensor 118, the narrow SWIR sensor 108, the laser rangefinder 116, the laser pointer 112, etc.) while the platform is in motion. In many cases the various sensors in pod or pay load, although they might have different FOVs, the center FOV of each sensor is aligned to the same direction, enabling the system to use different sensors for the same target location” (Benny, Page 25);
reconstructing a three-dimensional spectral model using the robot or the at least one sensor, wherein the three-dimensional spectral model comprises a three-dimensional volume including the locations within the three-dimensional space corresponding to the plurality of unique identifications “System 100 can utilize the atmospheric simulator to generate more than one un-calibrated multi-spectral data cube with known target material from a single given calibrated multi-spectral data cube using different atmospheric conditions, thus allowing to easily create a large training data set from a small number of calibrated multi-spectral data cubes which are labeled with known target materials and their location within the scene” (Benny, Page 18) where the model is a data cube and may be labeled with the material and location; and
Benny does not teach providing the plurality of unique identifications to the robot within the three-dimensional space, wherein the robot positions itself during an inspection of the production system by the robot within the three-dimensional space according to the locations within the three-dimensional space corresponding to the plurality of unique identifications;
maintaining at least a portion of each of the spectral markers at an invariant spectral value, wherein the spectral markers receive power to maintain the at least a portion at the invariant spectral value from within the three-dimensional space or from an outside or independent power source;
Nor does Benny teach displaying the three-dimensional volume.
Konolige teaches wherein the robot positions itself during an inspection of the production system by the robot within the three-dimensional space according to the locations within the three-dimensional space corresponding to the plurality of unique identifications “a virtual environment may be built up using a 3D volumetric or surface model to integrate information (e.g., from different sensors). This may allow the system to operate within a larger environment, such as in cases where one sensor may be insufficient to cover a large environment. Such techniques may also increase the level of detail captured, which may help the robotic device perform various tasks” (Konolige, ¶ [0066]) additionally, “The robotic arm may be configured to move through the scene as multiple views of the calibration pattern on the robotic arm are collected” (Konolige, ¶ [0080]). It is known in the art to have robots capable of navigating a scanned environment to perform tasks.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of producing 3-dimensional spectral models taught by Benny with the use of a robot capable to move about its 3-dimensional space taught by Konolige to produce a spectral observing robot capable of moving about the 3-dimentional space. The motivation to do so would be to observe more than what is immediately in the camera’s line of sight, or to see around object that are in the way.
Garsha teaches maintaining at least a portion of each of the spectral markers at an invariant spectral value, wherein the spectral markers receive power to maintain the at least a portion at the invariant spectral value from within the three-dimensional space or from an outside or independent power source “The power and temperature of the spectrum source 410 may be stabilized and monitored by closed-loop electronics and / or multi-bandpass filters 410a. The multi-bandpass filter 410a has n predetermined passbands and is positioned in front of the spectrum source 410. In an example embodiment of the invention, a spectrum acquisition system 422, eg, a microscope-based light acquisition device, includes or is coupled to a spectrum camera 443. The spectrum acquisition device 442 includes a scanning platform 445” (Garsha, Page 11) where maintaining a stable power of the spectrum source outputs a maintained spectrum;
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of producing 3-dimensional spectral models taught by Benny with the use of maintaining a constant spectral source taught by Garsha to produce a reference spectral output. The motivation to do so would be to compare the constant spectral output with other spectral signatures to identify differences.
Profio teaches displaying the three-dimensional volume “Thereafter, at 86, three-dimensional (3D) volume visualization is performed on the 2D stacks of images to form 3D volume visualization models. In particular, maximum intensity pixel projection is performed through each stack of 2D images resulting in a 3D MIP volume at each point in time.” (Profio, ¶ [027]) where taking 2D splices of an object using x-ray methods, then combining them produces a 3D model.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of producing 3-dimensional spectral models taught by Benny with the use of display taught by Profio to produce displays for multiple three-dimensional spectral models. The motivation to do so would be to observe multiple models.
Regarding claim 12, Benny in view of Profio and Garsha teach [t]he computing system of Claim 11, wherein the unique spectral signature of each of the spectral markers comprises a wavelength between 100nm and 15mm “In accordance with the presently disclosed subject matter, the real-time multi- spectral system 100 (also interchangeably referred to herein as "multi- spectral system 100" or as "system 100") can comprise a multi- spectral sensor 104 capable of capturing image data within specific wavelength ranges across the electromagnetic spectrum, for example: in visible (VIS) wavelengths, in ultraviolet (UV) wavelength, in Short-Wave Infrared (SWIR) wavelengths, in Near Infrared (NIR) wavelengths, in Middle Wavelength Infrared (MWIR) wavelengths, in Long Wavelength Infrared (LWIR) wavelengths, etc., or in any combination thereof” (Benny, Page 16) where it is known that UV, visible, and IR light have wavelengths on the electromagnetic spectrum between 100nm and 15mm, wherein each of the spectral markers comprises a two-dimensional shape “… a machine learning model capable of receiving: (a) a source 2D image of the 2D images of the scene, and (b) a target 2D image of the 2D images of the scene, and determining a corresponding flow map mapping changes to be made to pixels of the source 2D image in order to align the source 2D image with the target 2D image …” (Benny, Page 37) Where the target image is a two-dimensional representation of the target spectral signatures, which may be 2D, or 3D, and wherein each of the spectral markers comprises at least one portion that is reflective “each identified object is associated with: (i) a location within the scene, and (ii) a predetermined representative reflective spectral signature” (Benny, Page 36).
Regarding claim 14, Benny in view of Profio and Garsha teach [t]he computing system of Claim 11, wherein the operations performed by the computing system further comprises varying the unique spectral signature of at least one of the spectral markers over a period of time “The filter wheel is used to rotatably position a filter with a given wavelength range in the imaging path of the sensor to capture an image in that wavelength range. The filter in the imaging path of the sensor at a given time- window and/or interval of time is the active filter at that time window” (Benny, Page 16). Some materials are known to change in spectral signature over time, Benny discloses that a production system may be a field with strawberries, which can change as the plant grows (Benny, Page 26) additionally, it is known in the art that materials can be heated/ cooled to change temperature/ spectral signature, wherein varying the unique spectral signature comprises:
cyclically or non-cyclically varying the spectral signature that is emitted “Multi- spectral sensor 104 can alternatively comprise two or more filter wheels, which can be used to combine different filters from each of the filter wheels simultaneously. In addition, multi- spectral sensor 104 can alternatively utilize one or more of the following filter methods: (a) a Fabry-Perot interferometer (FPI), (b) a Linear Variable filter (LVF), and (c) a circular variable filter. Multi- spectral sensor 104 can be alternatively comprised of multiple sensors, each sensor captures images of the scene at a different wavelength range, or a combination of multiple sensors with filters enabling each sensor to capture different wavelength ranges” (Benny, Page 16) where using a different filter or method of reading the target is considered varying the observed spectral signature;
varying a wave amplitude or a frequency of the at least one of the spectral markers “In this setting the target spectral signature can be of a given agriculture product that system 100 is trying to identify and further investigate. For example, a spectral signature of a strawberry. The spectral signature of the strawberry is a vector associated with multiple values. Each value in this vector is associated with the spectral variation of reflectance or emittance of a strawberry in the wavelength ranges that can be captured by the multi-spectral sensor 104” (Benny, Page 26) where over a period of time spectral signatures of agricultural products can be changed and observed, additionally “The filter wheel is used to rotatably position a filter with a given wavelength range in the imaging path of the sensor to capture an image in that wavelength range. The filter in the imaging path of the sensor at a given time- window and/or interval of time is the active filter at that time window. The wheel is then turned to position the next filter, which has a different wavelength range in the imaging path of the sensor allowing the sensor to capture an image in the different wavelength range. Rotating the filter wheel allows the multi- spectral sensor 104 to capture a series of images in multiple wavelength ranges over a given time-frame.” (Benny, Page 16).
Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over Benny in view of Profio, Garsha, and further in view of Weimin Zhang (Pat. Pub. US-20190113445, herein after “Zhang”).
Regarding claim 15, Benny in view of Profio and Garsha teach [t]he computer system of Claim 11.
Benny in view of Profio and Garsha fail to explicitly teach wherein the operations performed by the computing system further comprises transmitting a supplemental data signal from at least one of the spectral markers to the one or more processors, wherein the supplemental data signal is comprised of at least one of the following: GPS data, humidity, detection or concentration of a gas, pressure, fluid level, or a combination thereof.
Zhang teaches wherein the operations performed by the computing system further comprises transmitting a supplemental data signal from at least one of the spectral markers to the one or more processors, wherein the supplemental data signal is comprised of at least one of the following: GPS data, humidity, detection or concentration of a gas, pressure, fluid level, or a combination thereof “Each infrared emission host 111 emits infrared rays to a corresponding infrared reflective assembly 112 to monitor the air mass in the monitored range of the monitoring equipment 11 in real time to obtain the infrared spectral data of the chemical factors in the passing air mass. The pollution factor qualitative module 12 presets the infrared judgment reference data of a plurality of pollution factors, which uses the infrared spectrum values of a plurality of different pollution factors as a reference” (Zhang, ¶ [0041]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of producing 3-dimensional spectral models taught by Benny with the transmission of certain data from the spectral marker taught by Zhang to read information directly from the spectral marker. The motivation to do so would be to analyze the status of the spectral marker or its surroundings, or to better communicate with the marker.
Response to Arguments
Applicant’s arguments with respect to claims 1, 3, 4, 6, 7, and 10 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.
Beginning on page 12 of the Remarks, Applicant argues that Benny fails to disclose the aspects of independent claim 1. The Applicant’s amendments add the robot’s capabilities to “position” itself within the three-dimensional space. The amendments may still be interpreted as simply angling or aligning the robot to observe the three-dimensional space. The Examiner understands the intended interpretation, as discussed during the interview, that “position” refers to physically moving within the three-dimensional space. Thus, the amendment overcomes the 35 U.S.C. § 102 rejection. After additional search, the amended claim is rejected under 35 U.S.C. § 103. The new rejection is applied to claims 2-4, 6, 7, 9-12, 14 and 15.
Applicant’s arguments, see Remarks, Page 14, filed April 9th, 2026, with respect to claims 5, 8, & 13 have been fully considered and are persuasive. The rejection of claims 5, 8 & 13 has been withdrawn.
Applicant’s arguments, see Remarks, Pages 17-19, filed April 9th, 2026, with respect to claims 16-20have been fully considered and are persuasive. The rejection of claims 16-20 has been withdrawn.
Allowable Subject Matter
Claims 16-20 allowed. Regarding claim 16, the prior art does not disclose a third area comprising a third spectral value which is lower relative to the first spectral value of the first area, wherein the first, second, and third areas of each of the spectral markers are arranged in a surface pattern that is unique to each of the spectral markers, wherein the second area comprises the second spectral value which is higher relative to a fourth spectral value of the at least one neutral area, and wherein the third area comprises the third spectral value which is lower relative to the fourth spectral value of the at least one neutral area, wherein the pattern of spectral values that is unique to each of the spectral markers is configured to provide a contrast between at least two areas of each spectral marker, wherein the at least one neutral area is comprised of a material configured to provide a contrast with the first, second, or third area, wherein the third area completely surrounds the first area and the second area completely surrounds the third area or wherein the first area completely surrounds the second area and the third area completely surrounds the first area, wherein the first area, the second area, and the third area are disposed in a common plane to form a two-dimensional shape (Emphasis added). The prior art does disclose the use of spectral taggant layers, which may change in signal or strength, but does not disclose that they are surrounded in the claimed pattern.
Regarding claims 17-20, the claims depend upon claim 16 and are therefore allowable.
Claims 5, 8, & 13 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
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 CAIDEN ALEXANDER USSERY whose telephone number is (571)272-1192. The examiner can normally be reached Monday - Friday* 7:30AM - 5PM, the examiner sincerely appreciates the applicant’s cooperation on the examiner’s first case.
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, Tammy Goddard can be reached at (571) 272-7773. 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.
/C.A.U./Examiner, Art Unit 2611
/TAMMY PAIGE GODDARD/Supervisory Patent Examiner, Art Unit 2611
Prosecution Insights