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 Interpretation 112(f)
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
As to claims 1-8, the “acquiring unit” is considered to read on a computer with a processor for operating the acquiring process (Specification as filed: Fig. 2; [0016] and [0020]; PGPUB: Fig. 2; [0028] and [0032]).
As to claims 1-8, the “discriminator” is considered to read on a computer with a processor for operating the discriminating process (Specification as filed: Fig. 2; [0016] and [0020]; PGPUB: Fig. 2; [0028] and [0032]).
As to claims 1-8, the “complementor” is considered to read on a computer with a processor for operating the complementing process (Specification as filed: Fig. 2; [0016] and [0020]; PGPUB: Fig. 2; [0028] and [0032]).
As to claims 1-8, the “determiner” is considered to read on a computer with a processor for operating the determining process (Specification as filed: Fig. 2; [0016] and [0020]; PGPUB: Fig. 2; [0028] and [0032]).
As to claims 3-8, the “simulation unit” is considered to read on a computer with a processor for operating the simulation process (Specification as filed: Fig. 2; [0016] and [0020]; PGPUB: Fig. 2; [0028] and [0032]).
As to claims 6-8, the “provider” is considered to read on a computer with a processor for operating the providing process (Specification as filed: Fig. 2; [0016] and [0020]; PGPUB: Fig. 2; [0028] and [0032]).
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 10 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because it claims a “control program” which is directed to non-statutory subject matter. One correction could be to state “A non-transitory storage medium storing a control program causing an electronic device to…”. Another way would be to state the device first, with the program being encoded/stored thereon. Appropriate correction is required.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1, 2, 9, and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Sasaki et al., US 2018/0321364 A1 (Sasaki) and further in view of RoyChowdhury et al., US 2022/0044034 A1 (RoyChowdhury).
Regarding claim 1, Sasaki teaches an electronic device (an apparatus for evaluating road surface properties) (Figs 1 and 2A; [0008]) comprising:
an acquiring unit configured to acquire (the road surface measuring apparatus 300 is provided with a scanner 310, which is a measuring apparatus) (Fig. 2A; [0064]) point cloud data corresponding to points on a road surface (wherein the measuring is received and point cloud data is produced to evaluate the road surface properties) ([0068]);
a discriminator configured to discriminate a missing part on the road surface (detecting a depression candidate) ([0079]), the missing part being located at a height equal to or lower than a ground surface of the road surface (wherein the missing part is lower than the road surface and satisfies an absolute value of the difference between each section and the section adjacent thereto) (Figs. 3B, 4B, and 6; [0078-0079]), the point cloud data of the missing part being not acquired (wherein full point cloud data is not created for the potential depression) ([0079]); and
a determiner configured to determine a recessed portion of the road surface (determining a depressed portion of the road surface, such as a pot hole or the like) ([0079]) based on the point cloud data (based on the point cloud data) (Figs. 9A and 9B; [0080-0083]).
However, Sasaki does not explicitly teach “a complementor configured to complement a pseudo point cloud at a position at a predetermined depth from the ground surface as a point cloud corresponding to the missing part” and using the pseudo point cloud to detect a recessed portion.
RoyChowdhury teaches a vehicle safety system (Abstract); wherein a LiDAR is used to capture three-dimensional points clouds ([0018]); wherein a complementor configured to complement a pseudo point cloud (generating a 3D point cloud only for the potential road damaged part) ([0020]) at a position at a predetermined depth from the ground surface (at a predetermined depth based on the camera data, wherein the point cloud is placed; feature of interest) ([0023-0024]) as a point cloud corresponding to the missing part (wherein a first model is used to identify regions of possible road damage; wherein a second model is used to classify each identified region, by overlaying a 3D point cloud data to the region(s) with road damage) ([0020]); and wherein the pseudo point cloud is used to detect a recessed portion of the road surface (wherein the point cloud is used to detect road damage such as potholes) ([0018], [0021], and [0028]).
It would have been obvious to one of ordinary skill in the art before the effective file date of the claimed invention to modify Sasaki to include only generating a pseudo point cloud for the “missing part / recessed portion” since by focusing only on a portion of the 3D point clouds the vehicle safety system avoids processing regions without road damage, further reducing the total processing time (RoyChowdhury; [0020]) and reducing overall resource consumption (e.g., fewer processor cycles/capacities, fewer memory blocks/storage units, etc.) and resource requirements (e.g., less processing power, less memory/storage space, etc.), thus improving overall performance time (RoyChowdhury; [0024]).
Regarding claim 2, Sasaki teaches
an electronic device (an apparatus for evaluating road surface properties) (Figs 1 and 2A; [0008]) comprising:
an acquiring unit configured to acquire (the road surface measuring apparatus 300 is provided with a scanner 310, which is a measuring apparatus) (Fig. 2A; [0064]) point cloud data indicating a set of points capable of identifying a state of a road surface (wherein the measuring is received and point cloud data is produced to evaluate the road surface properties) ([0068]);
a discriminator configured to discriminate a missing part of the point cloud data (detecting a depression candidate) ([0079]) which is located at a height equal to or lower than a height of the road surface in a detection range of the point cloud data (wherein the missing part is lower than the road surface and satisfies an absolute value of the difference between each section and the section adjacent thereto) (Figs. 3B, 4B, and 6; [0078-0079]); and
a determiner configured to determine a recessed portion of the road surface (determining a depressed portion of the road surface, such as a pot hole or the like) ([0079]) based on the point cloud data obtained (based on the point cloud data) (Figs. 9A and 9B; [0080-0083]).
However, Sasaki does not explicitly teach “a complementor configured to complement the missing part with a pseudo point cloud at a position at a predetermined depth from the road surface” and using the pseudo point cloud to detect a recessed portion.
RoyChowdhury teaches a vehicle safety system (Abstract); wherein a LiDAR is used to capture three-dimensional points clouds ([0018]); wherein a complementor configured to complement the missing part with a pseudo point cloud (generating a 3D point cloud only for the potential road damaged part) ([0020]) at a position at a predetermined depth from the road surface (at a predetermined depth based on the camera data, wherein the point cloud is placed; feature of interest) ([0023-0024]) as a point cloud corresponding to the missing part (wherein a first model is used to identify regions of possible road damage; wherein a second model is used to classify each identified region, by overlaying a 3D point cloud data to the region(s) with road damage) ([0020]); and wherein the pseudo point cloud is used to detect a recessed portion of the road surface (wherein the point cloud is used to detect road damage such as potholes) ([0018], [0021], and [0028]).
It would have been obvious to one of ordinary skill in the art before the effective file date of the claimed invention to modify Sasaki to include only generating a pseudo point cloud for the “missing part / recessed portion” since by focusing only on a portion of the 3D point clouds the vehicle safety system avoids processing regions without road damage, further reducing the total processing time (RoyChowdhury; [0020]) and reducing overall resource consumption (e.g., fewer processor cycles/capacities, fewer memory blocks/storage units, etc.) and resource requirements (e.g., less processing power, less memory/storage space, etc.), thus improving overall performance time (RoyChowdhury; [0024]).
Regarding claim 9, Sasaki teaches a method (a method) (Abstract) comprising:
by an electronic device (an apparatus for evaluating road surface properties) (Figs 1 and 2A; [0008]) to:
acquiring (the road surface measuring apparatus 300 is provided with a scanner 310, which is a measuring apparatus) (Fig. 2A; [0064]) point cloud data corresponding to points on a road surface (wherein the measuring is received and point cloud data is produced to evaluate the road surface properties) ([0068]);
discriminating a missing part on the road surface (detecting a depression candidate) ([0079]), the missing part being located at a height equal to or lower than a ground surface of the road surface (wherein the missing part is lower than the road surface and satisfies an absolute value of the difference between each section and the section adjacent thereto) (Figs. 3B, 4B, and 6; [0078-0079]), the point cloud data of the missing part being not acquired (wherein full point cloud data is not created for the potential depression) ([0079]); and
determining a recessed portion of the road surface (determining a depressed portion of the road surface, such as a pot hole or the like) ([0079]) based on the point cloud data (based on the point cloud data) (Figs. 9A and 9B; [0080-0083]).
However, Sasaki does not explicitly teach “a complementor configured to complement a pseudo point cloud at a position at a predetermined depth from the ground surface as a point cloud corresponding to the missing part” and using the pseudo point cloud to detect a recessed portion.
RoyChowdhury teaches a vehicle safety system (Abstract); wherein a LiDAR is used to capture three-dimensional points clouds ([0018]); wherein complementing a pseudo point cloud (generating a 3D point cloud only for the potential road damaged part) ([0020]) at a position at a predetermined depth from the ground surface (at a predetermined depth based on the camera data, wherein the point cloud is placed; feature of interest) ([0023-0024]) as a point cloud corresponding to the missing part (wherein a first model is used to identify regions of possible road damage; wherein a second model is used to classify each identified region, by overlaying a 3D point cloud data to the region(s) with road damage) ([0020]); and wherein the pseudo point cloud is used to detect a recessed portion of the road surface (wherein the point cloud is used to detect road damage such as potholes) ([0018], [0021], and [0028]).
It would have been obvious to one of ordinary skill in the art before the effective file date of the claimed invention to modify Sasaki to include only generating a pseudo point cloud for the “missing part / recessed portion” since by focusing only on a portion of the 3D point clouds the vehicle safety system avoids processing regions without road damage, further reducing the total processing time (RoyChowdhury; [0020]) and reducing overall resource consumption (e.g., fewer processor cycles/capacities, fewer memory blocks/storage units, etc.) and resource requirements (e.g., less processing power, less memory/storage space, etc.), thus improving overall performance time (RoyChowdhury; [0024]).
Regarding claim 10, Sasaki teaches a control program (CPU carry out a program) ([0069]) causing an electronic device (an apparatus for evaluating road surface properties) (Figs 1 and 2A; [0008]) to:
acquire (the road surface measuring apparatus 300 is provided with a scanner 310, which is a measuring apparatus) (Fig. 2A; [0064]) point cloud data corresponding to points on a road surface (wherein the measuring is received and point cloud data is produced to evaluate the road surface properties) ([0068]);
discriminate a missing part on the road surface (detecting a depression candidate) ([0079]), the missing part being located at a height equal to or lower than a ground surface of the road surface (wherein the missing part is lower than the road surface and satisfies an absolute value of the difference between each section and the section adjacent thereto) (Figs. 3B, 4B, and 6; [0078-0079]), the point cloud data of the missing part being not acquired (wherein full point cloud data is not created for the potential depression) ([0079]); and
determine a recessed portion of the road surface (determining a depressed portion of the road surface, such as a pot hole or the like) ([0079]) based on the point cloud data (based on the point cloud data) (Figs. 9A and 9B; [0080-0083]).
However, Sasaki does not explicitly teach “a complementor configured to complement a pseudo point cloud at a position at a predetermined depth from the ground surface as a point cloud corresponding to the missing part” and using the pseudo point cloud to detect a recessed portion.
RoyChowdhury teaches a vehicle safety system (Abstract); wherein a LiDAR is used to capture three-dimensional points clouds ([0018]); wherein complement a pseudo point cloud (generating a 3D point cloud only for the potential road damaged part) ([0020]) at a position at a predetermined depth from the ground surface (at a predetermined depth based on the camera data, wherein the point cloud is placed; feature of interest) ([0023-0024]) as a point cloud corresponding to the missing part (wherein a first model is used to identify regions of possible road damage; wherein a second model is used to classify each identified region, by overlaying a 3D point cloud data to the region(s) with road damage) ([0020]); and wherein the pseudo point cloud is used to detect a recessed portion of the road surface (wherein the point cloud is used to detect road damage such as potholes) ([0018], [0021], and [0028]).
It would have been obvious to one of ordinary skill in the art before the effective file date of the claimed invention to modify Sasaki to include only generating a pseudo point cloud for the “missing part / recessed portion” since by focusing only on a portion of the 3D point clouds the vehicle safety system avoids processing regions without road damage, further reducing the total processing time (RoyChowdhury; [0020]) and reducing overall resource consumption (e.g., fewer processor cycles/capacities, fewer memory blocks/storage units, etc.) and resource requirements (e.g., less processing power, less memory/storage space, etc.), thus improving overall performance time (RoyChowdhury; [0024]).
Claim(s) 3-8 are rejected under 35 U.S.C. 103 as being unpatentable over Sasaki et al., US 2018/0321364 A1 (Sasaki), RoyChowdhury et al., US 2022/0044034 A1 (RoyChowdhury), and further in view of Ren et al., “An Improved Cloth Simulation Filtering Algorithm Based on Mining Point Cloud” (Ren).
Regarding claim 3, Sasaki teaches an acquiring unit configured to acquire (the road surface measuring apparatus 300 is provided with a scanner 310, which is a measuring apparatus) (Fig. 2A; [0064]) point cloud data corresponding to points on a road surface (wherein the measuring is received and point cloud data is produced to evaluate the road surface properties) ([0068]). RoyChowdhury teaches a vehicle safety system (Abstract); wherein a LiDAR is used to capture three-dimensional points clouds ([0018]); and wherein complementing a pseudo point cloud (generating a 3D point cloud only for the potential road damaged part) ([0020]).
However, neither explicitly teaches a cloth simulation.
Ren teaches an improved cloth simulation filtering algorithm for unmanned driving system based on the cloth simulation filtering algorithm (p. 1; Abstract); and wherein further comprising a cloth simulation unit (cloth simulation filtering algorithm) (p. 1; Abstract) configured to output a shape of a virtual cloth (piece of “cloth” which is constructed by virtual particles) (pages 1-2; Fig. 1 and Section A.) when the point cloud data is covered with the virtual cloth (wherein the point cloud data is covered by the virtual cloth) (pages 1-2; Fig. 1 and Section A.) having a predetermined tensile force with a predetermined gravity (having predetermined gravity and external and internal forces) (pages 1-2; Fig. 1 and Section A.), wherein the determiner determines the recessed portion of the road surface using the shape of the virtual cloth output by the cloth simulation unit and the complemented pseudo point cloud (using the virtual cloth and the point cloud data detected for determining the recessed (pits) portion of the road surface) (page 3; Fig. 5, 2nd and 3rd paragraphs and pages 3-4; Section III.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of prior arts to include using a cloth simulation since it improves the detection accuracy for road conditions (Ren; pages 3-4, Section III., 2nd paragraph).
Regarding claim 4, Ren teaches wherein the cloth simulation unit (cloth simulation filtering algorithm) (p. 1; Abstract) is configured to output the shape of the virtual cloth (piece of “cloth” which is constructed by virtual particles) (pages 1-2; Fig. 1 and Section A.) by determining whether or not to fix a cloth lattice point to the point cloud (wherein the position of the particles can be adjusted; fixed to the point cloud as immovable) (p. 3; Figs. 4 and 5, 1st-3rd paragraphs) such that a bendable cloth shape (wherein the position of the particles of the cloth can be adjusted) (p. 3; 2nd paragraph) is formed between a first point that is highest in a height direction and a second point that is located around the first point and is lower than the first point in the height direction among the points in the point cloud (searches for the point with the highest elevation value in each grid, and floats a certain height as the elevation value of virtual particles in the grid, which is called uneven initialization) (p. 3; Fig. 4, 1st paragraph), when the cloth lattice point of the virtual cloth is brought close to the point cloud indicated by the point cloud data with a predetermined gravity (wherein the virtual cloth is brought close to the point cloud based on forces and gravity) (pages 1-2; Section A. and p. 3; Fig. 5, 2nd and 3rd paragraphs).
Regarding claim 5, teaches RoyChowdhury teaches a height of the point cloud data (a height measurement) ([0055]), a climbable angle of the mobile body (an incident angle to the road surface of the vehicle) (Fig. 2A; [0064] and [0106]), and a minimum altitude calculated from the detection range (within a detection range) ([0057]) and the climbable angle (an incident angle to the road surface of the vehicle) (Fig. 2A; [0064] and [0106]).
However, Sasaki does not explicitly teach “wherein the acquiring unit is configured to acquire the point cloud data based on a depth image obtained by a detector (mounted on a mobile body measuring the road surface”.
RoyChowdhury teaches wherein the acquiring unit is configured to acquire the point cloud data (acquiring a 3D point cloud) ([0024]) based on a depth image obtained by a detector (depth image based on the camera) ([0023]) mounted on a mobile body measuring the road surface (wherein the camera is mounted on a vehicle measuring the road, for example, for road damage such as potholes, etc.) (Fig. 1A; Abstract and [0021-0022]), and a height of the pseudo point cloud is set based on a detection range of the point cloud data (based on the depth range for an identified region of actual road damage) ([0028]).
It would have been obvious to one of ordinary skill in the art before the effective file date of the claimed invention to modify Sasaki to include only generating a pseudo point cloud for the “missing part / recessed portion”, based off of a depth image, since by focusing only on a portion of the 3D point clouds the vehicle safety system avoids processing regions without road damage, further reducing the total processing time (RoyChowdhury; [0020]) and reducing overall resource consumption (e.g., fewer processor cycles/capacities, fewer memory blocks/storage units, etc.) and resource requirements (e.g., less processing power, less memory/storage space, etc.), thus improving overall performance time (RoyChowdhury; [0024]).
Regarding claim 6, Sasaki teaches further comprising a provider configured to provide provision data capable of identifying the recessed portion of the road surface determined by the determiner (providing data that shows the detection of a depression candidate on the road) (Figs. 9A and 9B; [0076] and [0082]). RoyChowdhury teaches further comprising a provider configured to provide provision data capable of identifying the recessed portion of the road surface determined by the determiner (the vehicle safety system outputs information for display on a display device; including an alert symbol indicating road damage, such as “POTHOLE DETECTED IN 20 METERS”.) (Figs. 5A and 5B; [0082]).
Regarding claim 7, Sasaki teaches wherein the provider is configured to provide the provision data to the mobile body (wherein the data is provided to the vehicle) ([0082]). RoyChowdhury teaches wherein the provider is configured to provide the provision data to the mobile body (wherein the data is sent to the vehicle) ([0019] and [0082]).
Regarding claim 8, RoyChowdhury teaches wherein the acquiring unit is configured to acquire posture data of the mobile body (wherein the posture of the body of the vehicle is known so that a dampening of the suspension can occur what a pothole is detected) (Fig. 6; [0084-0085]), and the complementor is configured to complement the missing part with a pseudo point cloud (generating a 3D point cloud only for the potential road damaged part) ([0020]) at a position at a predetermined depth from the road surface (at a predetermined depth based on the camera data, wherein the point cloud is placed; feature of interest) ([0023-0024]) based on the posture data (based on the posture of the vehicle; i.e. how the vehicle sits on the road) ([0023-0024] and [0084-0085]).
Contact
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL J VANCHY JR whose telephone number is (571)270-1193. The examiner can normally be reached Monday - Friday 9am - 5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Emily Terrell can be reached at (571) 270-3717. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MICHAEL J VANCHY JR/Primary Examiner, Art Unit 2666 Michael.Vanchy@uspto.gov
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