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 .
Information Disclosure Statement
The information disclosure statements (IDSs) were submitted on 10/20/2023, 11/19/2024 and 04/07/2025. The submissions are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
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.
The current 35 USC 101 analysis is based on the current guidance (Federal Register vol. 79, No. 241. pp. 74618-74633). The analysis follows several steps. Step 1 determines whether the claim belongs to a valid statutory class. Step 2A prong 1 identifies whether an abstract idea is claimed. Step 2A prong 2 determines whether any abstract idea is integrated into a practical application. If the abstract idea is integrated into a practical application the claim is patent eligible under 35 USC 101. Last, step 2B determines whether the claims contain something significantly more than the abstract idea. In most cases the existence of a practical application predicates the existence of an additional element that is significantly more.
The 35 USC 101 analysis between each element of claims and its combination is presented in the table below
Claim number and elements
Judicial exception (Step 2A Prong one)
Practical application (Step 2A Prong two)/ Significantly more (Step 2B)
Claim 1
Step 1: Yes, statutory class
Step 2A Prong two: No / Step 2B: No
An obstacle detection apparatus configured to compute a position of an obstacle from point clouds acquired by one or more sensors, the obstacle detection apparatus performing the processing of:
Step2A Prong one: Yes
“both communicate with IoT device ~”, “receive data streams ~”, “reconcile differences in communication protocols~” are
plotting point clouds acquired by one or more sensors on a plane;
“plotting point clouds …” is insignificant extra-solution activities to collect routine data used for perform mathematical processes.
“one or more sensors” are high level of generalities to perform a generic computer function of a generic computer component.
extracting, from the point clouds plotted on the plane, a point cloud whose degree of density is equal to or larger than a predetermined degree of density; and
abstract idea
mathematical concept
“extracting ~” is a math process to choose routine data used for a mathematical calculation.
“a predetermined degree of density” is a mathematical concept/value.
computing a position of an obstacle from the extracted point cloud.
abstract idea
mental process or mathematical concept
“computing a position …” is a math process to calculate a position value based on the extracted point cloud (i.e., mathematical value).
Claims 1-8 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 1-8 are directed to an abstract idea. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception as addressed below and presented in the above table.
Step 2A: Prong One
Regarding Claim 1, the limitations recited in Claim 1, as drafted, are processes that, under its broadest reasonable interpretation, cover performance of the limitation in the mathematical calculations and/or the mind, as presented in the above table. Nothing in the claim elements precludes the step from practically being performed in the mind and/or the mathematical calculations. For example, “extracting, from the point clouds plotted on the plane, a point cloud whose degree of density is equal to or larger than a predetermined degree of density” in the context of this claim may encompass manually
calculating or inferring the point cloud by performing a mathematical calculation, where the point cloud’s degree of density is equal to or larger than a predetermined degree of density based on the collected data (i.e., points clouds acquire by the sensors). (See at least lines 3-23 of page 6 in the instant application) (MPEP 2106.04(a)(2)). The point cloud’s degree of density and the predetermined degree of density are both indicative of a mathematical concept/value/amount. For example, “computing a position of an obstacle from the extracted point cloud” in the context of this claim may encompass manually calculating or inferring the position of the obstacle based on the extracted point cloud, which is indicative of a mathematical value/concept/coordination. (See at least lines 3-23 of page 6 in the instant application) (MPEP 2106.04(a)(2)).
Step 2A: Prong Two
This judicial exception is abstract ideal itself and not integrated into a practical application. In particular, the specification details use of a computer to perform mathematical calculations of “extracting, from the point clouds plotted on the plane, a point cloud whose degree of density is equal to or larger than a predetermined degree of density” and “computing a position of an obstacle from the extracted point cloud”. The limitation of “plotting point clouds acquired by one or more sensors on a plane” is insignificant extra-solution activity necessary to merely gather data (i.e., point clouds) scanned by the sensors to be used for performing the abstract idea of the mathematical calculations as set forth above. See MPEP 2106.05(g). The one or more sensors are recited at high-level of generalities to merely gather routine data (i.e., point clouds) scanned by the sensors. Claim 1 does not present tangible or physical elements/components and/or integration of improvements to be indicative of specific features/structure/acts how and or with what to compute a position of an obstacle from point clouds. (See MPEP 2106.04(d)). Claim 1 does not present a technical solution to a technical problem by providing an improvement to the functioning of computer, or to any other technology or technical field related to computing a position of an obstacle from point clouds. (See MPEP 2106.04(d)). Therefore, there is no showing of integration into a practical application such as an improvement to the functioning of a computer, or to any other technology or technical field, or use of a particular machine.
Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The limitation of “plotting point clouds acquired by one or more sensors on a plane” is an insignificant pre-solution activity to merely gather routine data (i.e., point clouds) to be used for performing the abstract idea. See MPEP 2106.05(g). Therefore, the functions and/or structures related to the “sensors” are well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality to the judicial exception, as the Korchev reference (US 20160063754 A1) teaches. See MPEP 2106.05(d). As discussed above, with respect to integration of the abstract idea into a practical application, using the processing circuity of the sensor to perform “plotting point clouds acquired by one or more sensors on a plane”, “extracting, from the point clouds plotted on the plane, a point cloud whose degree of density is equal to or larger than a predetermined degree of density” and “computing a position of an obstacle from the extracted point cloud” amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept cannot provide statutory eligibility. Claim 1 is not patent eligible.
Regarding Claims 2-6, the limitations are further directed to an abstract idea, as described in claim 1. The additional elements of the “mobile robot” in claim 2 and the “Light Detection And Ranging (LiDAR) or a depth camera” in claim 5 are high level of generalities merely recited to perform abstract idea and perform a generic computer function of a generic computer component. The limitation of “a point cloud whose number of points in any one of a plurality of grids defined in a matrix on a plane” in claim 3 is further directed to an abstract idea, where the plurality of grids is indicative of a mathematical concept/value coordination which may be performed by a mathematical algorithm/software.
Regarding Claim 7, it is a method type claim having similar limitations as of claim 1 above. Therefore, it is rejected under the same rationale as of claim 1 above.
Regarding Claim 8, it is a non-transitory computer readable storage medium type claim having similar limitations as of claim 1 above. Therefore, it is rejected under the same rationale as of claim 1 above. The additional element of the computer is a high-level of generality recited to merely perform a generic computer function of a generic computer component.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
1. Claims 1-3 and 5-8 are rejected under 35 U.S.C. 103 as being unpatentable over Yoshida et al. (US 20110164037 A1, hereinafter referred to as “Yoshida” in IDS filed 11/19/2024) in view of ROCHAN MEGANATHAN et al. (US 20190236381 A1, hereinafter referred to as “ROCHAN”).
Regarding Claim 1, Yoshida teaches an obstacle detection apparatus configured to compute a position of an obstacle (standing feature) from point clouds acquired by one or more sensors (Para 0009-0014), the obstacle detection apparatus performing the processing of:
plotting point clouds acquired by one or more sensors (Fig. 1, laser scanner 210) on a plane (Abstract, “acquire a distance and orientation point cloud, a camera image, GPS observation information, a gyro measurement value, and an odometer measurement value, while moving in a target area … generate a point cloud based on the camera image, the distance and orientation point cloud, and a position and attitude localized value”; Para 0010, “projecting each point of the 3D point cloud onto a plane based on the 3D coordinates of each point indicated by the 3D point cloud by using CPU”);
extracting, from the point clouds plotted on the plane, a point cloud whose degree of density is equal to or larger than a predetermined degree of density (Abstract, “extract points close to a road surface exclusively from the point cloud by removing points higher than the road surface, orthographically project each extracted point onto a horizontal plane”; Para 0009, “remove unnecessary points from a massive number of acquired laser points, and extract necessary laser points”; Para 0011-0012 “extract from the 3D point cloud as a predetermined height point cloud a point whose height is within a predetermined height range based on the 3D coordinates of each point indicated by the 3D point cloud … to calculate a point density of each point of the 3D point cloud projected onto the plane”).
Regarding “computing a position of an obstacle from the extracted point cloud”, Yoshida teaches specifying and generating an image portion including an obstacle from the extracted point cloud, but fails to explicitly disclose computing a position of an obstacle (Para 0012, “specify an image portion of the aerial image showing a standing feature based on the point density calculated by the point density calculating section …. generate the aerial image in which the image portion specified by the standing feature specifying section).
However, ROCHAN teaches computing a position of an obstacle from the extracted point cloud (Para 0006 “extract one or more regions comprising one or more obstacles, from the disparity image, determine boundary points of each of the one or more obstacles, for determining a position of each of the one or more obstacles in terms of image co-ordinates … determine a gradient for each of the point cloud data points to determine a structural orientation of the one or more obstacles”).
Yoshida and ROCHAN are both considered to be analogous to the claimed invention because they are in the same field of detecting obstacles using point cloud data. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Yoshida to incorporate the teachings of ROCHAN by providing operations for calculating a position of an obstacle from the extracted point cloud data, taught by ROCHAN at least at paragraph 0006.
Regarding Claim 2, Yoshida teaches wherein the one or more sensors are attached to a mobile robot (Fig. 2, mobile measuring apparatus 200), and the obstacle detection apparatus plots the point clouds acquired by the one or more sensors on the plane including a surface on which the mobile robot moves (Para 0010, “generate an aerial image of a ground surface by using a 3D point cloud indicating 3D coordinates of a spot on the ground. The aerial image generating apparatus may include a 3D point cloud projecting section that is configured to generate the aerial image by projecting each point of the 3D point cloud onto a plane based on the 3D coordinates of each point indicated by the 3D point cloud”; Para 0064, “vehicle 202 moves around on the roads in a target area of measurement”).
Regarding Claim 3, “wherein the obstacle detection apparatus extracts, from the point clouds plotted on the plane, a point cloud whose number of points in any one of a plurality of grids defined in a matrix on a plane is equal to or larger than a predetermined number as the point cloud whose degree of density is equal to or larger than the predetermined degree of density”, Yoshida teaches a point cloud having a predetermined number or more of points (Para 0184, “ The point density calculating section 160 calculates by using CPU a point density 169a of the point cloud orthoimage 191 generated by the point cloud projecting section 110 for each zone of the point cloud orthoimage 191 divided into zones of a predetermined size) and occupying any of a plurality of grids (i.e., area, Para 0065, “acquires the distance and orientation point cloud 291 of measured features in the target area of measurement”) defined in a matrix on the plane is extracted as a point cloud having a density equal to or higher than the predetermined density (Para 0193 -0197, “divides the projected plane into zones of a predetermined size, and calculates the point density 169a of each point of the point cloud 491 for each zone …. The "point density 169a" is assumed to be the number of points of the point cloud 491 projected onto the minute zone … the standing feature image portion 179a each minute zone whose point density 169a calculated in S142B is the same or more than a predetermined number … the point density 169a of a standing feature is higher than the point density 169a of a road surface …”).
Regarding Claim 5, Yoshida fails to explicitly disclose, but ROCHAN teaches wherein the sensor is any one of Light Detection and Ranging (LiDAR) or a depth camera (Para 0002, “sensors such as laser, Light Detection and Ranging (LIDAR), computer vision, camera and the like … the existing autonomous vehicle uses only LIDAR sensors for obstacle detection”).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Yoshida to incorporate the teachings of ROCHAN by providing sensors such as Light Detection and Ranging (LiDAR) or camera, taught by ROCHAN at least at paragraph 0002.
Regarding Claim 6, it is a system type claim merely reciting claim 2. Therefore, it is rejected under the same rationale as of claim 2 above.
Regarding Claim 7, it is a method type claim having similar limitations as of claim 1 above. Therefore, it is rejected under the same rationale as of claim 1 above.
Regarding Claim 8, it is a non-transitory readable storage medium claim having similar limitations as of claim 1 above. Therefore, it is rejected under the same rationale as of claim 1 above. The additional elements of the control program and the computer are taught by at least paragraphs 0098-0099 and 0103 of Yoshida.
2. Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Yoshida in view of ROCHAN and further in view of YI et al. (CN 112595258 A, hereinafter referred to as “YI” in IDS file 4/7/2025).
Regarding Claim 4, Yoshida teaches wherein the obstacle detection apparatus removes, from the point clouds plotted on the plane, a point cloud whose degree of density is smaller than the predetermined degree of density as … (Para 0009, “remove unnecessary points from a massive number of acquired laser points, and extract necessary laser points”; Para 0193 -0197, “divides the projected plane into zones of a predetermined size, and calculates the point density 169a of each point of the point cloud 491 for each zone …. The "point density 169a" is assumed to be the number of points of the point cloud 491 projected onto the minute zone … the standing feature image portion 179a each minute zone whose point density 169a calculated in S142B is the same or more than a predetermined number … the point density 169a of a standing feature is higher than the point density 169a of a road surface …”).
Under the broadest reasonable interpretation (BRI), Yoshida teaches removing unnecessary points to extract necessary laser points based on the specific condition (i.e., “same or more than a predetermined number” taught in paragraphs 0193-0197). Yoshida in view of ROCHAN fails to explicitly disclose removing a point cloud as a noise component. However, YI teaches disclose removing a point cloud as a noise component when the point cloud less than the critical value (“the point cloud data amount obtained by three-dimensional laser scanning is very large and doped with other redundant information; how to quickly remove noise from the large data; extracting the building profile and quickly establishing the corresponding three-dimensional mode … distinguishing the ground object and the noise by point cloud projection density method; extracting the grid of the geometric position boundary of the ground object and fitting the analysis equation of the geometric position boundary the scanned point cloud is removed with a few noise or shielding … deleting the point cloud corresponding to the grid network less than the critical value” in pages 2, 7 of English machine translation)
YI is considered to be analogous to the claimed invention because it is in the same field of a ground object outline extracting method of point cloud. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Yoshida in view of ROCHAN to incorporate the teachings of YI by providing operations for removing a point cloud as a noise component when the point cloud less than the critical value (i.e., predetermined degree of density), taught by UI at least at pages 2 and 7 of English machine translation.
Citation of Pertinent Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Korchev et al. (US 20160063754 A1) teaches detecting an opening in a structure represented by a three-dimensional point cloud may include the steps of: (1) creating a three-dimensional point cloud map of a scene, the three-dimensional point cloud map including a plurality of points representing a ground plane and the structure upon the ground plane, (2) identifying an absence of points within the plurality of points representing the structure, and (3) determining whether the absence of points represents the opening in the structure.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BYUNG RO LEE whose telephone number is (571)272-3707. The examiner can normally be reached on Monday-Friday 8:30am-4:00pm.
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/BYUNG RO LEE/Examiner, Art Unit 2858
/LEE E RODAK/Supervisory Patent Examiner, Art Unit 2858