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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 05/16/24 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Drawings
The drawings are objected to because no reference numbers were given for the various blocks in figures 1-5. Please ensure that no reference numbers were inadvertently omitted from either the specification and/or drawings. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
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.
Claims 1-10 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.
With respect to step 1 of the patent subject matter eligibility analysis, the claims are directed to a process, machine, manufacture, or composition of matter. Independent claim 1 is directed to a method for detecting a retaining wall, which is a process. All other claims depend on independent claims 1. As such, claims 1-10 are directed to a statutory category.
With respect to step 2A, prong one, the claims recite an abstract idea, law of nature, or natural phenomenon. Specifically, the following limitations recite mathematical concepts and/or mental processes.
Claim 1
processing the original data to obtain finally processed data of the retaining wall (General processing of data recites an observation, evaluation, judgment, and/or opinion that can be performed in the human mind. As the claims are currently recited, “thinking about” the data would satisfy the claimed processing, as details about the nature of the processing are not claimed. However, upon consideration of the applicant’s original specification, it would appear that the processing is performed by the implementation of specific mathematical equations and/or relationships (see paragraphs 00139-00146). As such, the limitation recites abstract mental processes and/or mathematical concepts.)
sequentially performing ground determination and ground elimination on the ground data to obtain non-ground point cloud data (This limitation recites an observation, evaluation, judgment, and/or opinion that can be performed in the human mind. As the claims are currently recited, “thinking about” or “envisioning” data points that constitute ground and then eliminating them from consideration is a consideration that can be performed in the human mind.)
obtaining distance information between a rear end of the vehicle and the retaining wall and integrity data of the retaining wall by calculation according to the finally processed data of the retaining wall and the non-ground point cloud data (This limitation recites specific calculation. The limitation therefore recites an abstract mathematical concept.)
Claim 10
processing the original data to obtain finally processed data of the retaining wall (General processing of data recites an observation, evaluation, judgment, and/or opinion that can be performed in the human mind. As the claims are currently recited, “thinking about” the data would satisfy the claimed processing, as details about the nature of the processing are not claimed. However, upon consideration of the applicant’s original specification, it would appear that the processing is performed by the implementation of specific mathematical equations and/or relationships (see paragraphs 00139-00146). As such, the limitation recites abstract mental processes and/or mathematical concepts.)
sequentially performing ground determination and ground elimination on the ground data to obtain non-ground point cloud data (This limitation recites an observation, evaluation, judgment, and/or opinion that can be performed in the human mind. As the claims are currently recited, “thinking about” or “envisioning” data points that constitute ground and then eliminating them from consideration is a consideration that can be performed in the human mind.)
obtaining distance information between a rear end of the vehicle and the retaining wall and integrity data of the retaining wall by calculation according to the finally processed data of the retaining wall and the non-ground point cloud data (This limitation recites specific calculation. The limitation therefore recites an abstract mathematical concept.)
Dependent claims 2-9 depend on independent claim 1. They recite the independent claims’ abstract limitations, by virtue of their dependence. In addition, some of the claims also recite their own abstract mathematical concepts and/or mental processes.
Claim 3 discloses, “determining whether a distance from a coordinate of a point in point cloud data … is less than a preset distance … determining the point … that needs to be filtered out … determining the point that needs to be reserved …” Considering a binary decision is an observation, evaluation, judgment, and/or opinion that can be performed in the human mind. The limitation therefore recites an abstract mental process. Claim 3 also discloses other forms of “determination,” which are also binary decisions that can be performed in the human mind.
Claim 3 further discloses performing coordinate transformation of different types, which recite abstract mathematical relationships and/or calculations. Claim 3 also discloses filtering, which can be both a simple mental process and/or an abstract mathematical concept.
Claim 4 further discloses abstract mathematical concepts and/or mental processes, in the form of determinations, for similar reasons as discussed above.
Claim 5 discloses converting non-ground point cloud data into a well-ordered set, which recites abstract mathematical relationships and/or calculations. Claim 5 also explicitly discloses, “calculating the distance information …” which is a specific mathematical calculation. The claimed limitation of “determining the integrity data” also recites an abstract mental process (when determination is considered in a general sense) and/or an abstract mental process (when the determination is defined by specific mathematical calculations and relationships).
Claim 6 recites an abstract mathematical concept, in the form of a specific mathematical equation/formula.
Claim 7 recites abstract mathematical concepts, in the form of assigning specific variables to represent mathematical relationships.
Claim 8 recites abstract mathematical concepts. In the form of performing various calculations involving the variables disclosed in claim 7.
Claim 9 recites abstract mathematical concepts, in the form of performing various calculations, involving the variables disclosed in claims 7-8. The final determination based on a binary decision involving a threshold is an abstract mental process that can be performed in the human mind.
With respect to step 2A, prong two, the claims do not recite additional elements that integrate the judicial exception into a practical application. The following limitations are considered “additional elements” and explanation will be given as to why these “additional elements” do not integrate the judicial exception into a practical application.
Claim 1
A method for detecting a retaining wall suitable for an automatic driving vehicle (The general intended use of “detecting a retaining wall suitable for an automatic driving vehicle” merely serves to generally link the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)). It is not indicative of integration into a practical application.)
obtaining original data acquired during a backing process of a vehicle and used for detecting a retaining wall (General and generic data collection, for the purposes of data processing, merely adds insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g)). It is not indicative of integration into a practical application. Furthermore, the general and generic mention of “a backing process of a vehicle” and “used for detecting a retaining wall” merely serves to generally link the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)).)
obtaining ground data during the backing process of the vehicle (General and generic data collection, for the purposes of data processing, merely adds insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g)). It is not indicative of integration into a practical application. Furthermore, the general and generic mention of “during the backing process of the vehicle” merely serves to generally link the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)).)
Claim 10
A system for detecting a retaining wall suitable for an automatic driving vehicle (The general intended use of “detecting a retaining wall suitable for an automatic driving vehicle” merely serves to generally link the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)). It is not indicative of integration into a practical application.)
a data acquisition module used for obtaining original data acquired during a backing process of a vehicle and used for detecting a retaining wall (General and generic data collection, for the purposes of data processing, merely adds insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g)). It is not indicative of integration into a practical application. Furthermore, the general and generic mention of “a backing process of a vehicle” and “used for detecting a retaining wall” merely serves to generally link the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)). Furthermore, the disclosure of “a data acquisition module” appears to merely recite a generic computer component and merely use a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)), which is not indicative of integration into a practical application.)
a data screening module used for obtaining ground data during the backing process of the vehicle (see MPEP 2106.05(g)). It is not indicative of integration into a practical application. Furthermore, the general and generic mention of “during the backing process of the vehicle” merely serves to generally link the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)). Furthermore, the disclosure of “a data screening module” appears to merely recite a generic computer component and merely use a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)), which is not indicative of integration into a practical application.)
a feature extraction module (The disclosure of “a data screening module” appears to merely recite a generic computer component and merely use a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)), which is not indicative of integration into a practical application.)
Dependent claims 2-9 depend on independent claim 1. They recite the independent claims’ limitations that are not indicative of integration into a practical application, by virtue of their dependence. In addition, some of the claims also recite their own limitations that are not indicative of integration into a practical application.
Claim 2 discloses that, “the original data include attitude information and motion state information of the vehicle and point cloud data related to the retaining wall behind the automatic driving vehicle.” This limitation merely gives technological context to the type of data that is processed. It generally links the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)).
With respect to step 2B, the claims do not recite additional elements that amount to significantly more than the judicial exception. The claimed invention does not add significantly more because, as discussed above in step 2A, prong two, the claims do nothing more than merely use a computer as a tool to perform an abstract idea; add insignificant extra-solution activity to the judicial exception; and/or generally link the use of the judicial exception to a particular technological environment or field of use. The claims are directed to receiving and processing data. This is well-understood, routine, and conventional. Simply appending well-understood, routine, and conventional activities previously known to the industry, and specified at a high level of generality, to the judicial exception is not indicative of an inventive concept (aka “significantly more”) (see MPEP 2106.05(d) and Berkheimer Memo).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-2, 4-5, and 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Tezuka Daiki (JP2019178972A) in view of Kumar et al (US Pat 11668798). Please note that an English abstract for JP2019178972A was included in the 05/16/24 IDS. Here, the examiner has included both the original foreign document and full machine translation.
With respect to claim 1, Tezuka Daiki discloses:
A method for detecting a retaining structure suitable for an automatic driving vehicle (figures 1-2; abstract; reference 1002; paragraph 0086 discloses, “to detect the shape of obstacles behind them …”; paragraph 0087 states, “… that drives autonomously, the output may be sent to an autonomous driving control device that controls autonomous driving, and the autonomous driving control device may perform calculations necessary for stopping …”)
obtaining original data acquired during a backing process of a vehicle and used for detecting a retaining structure, and processing the original data to obtain finally processed data of the retaining structure (paragraph 0006 states, “The present invention relates to a reverse assist device for a work machine that assists the reverse movement of the work machine … and receive reflected light reflected from an object to be detected to measure the distance to the object to be detected … and the reverse assist device for a work machine is characterized in that it detects the distance to a wheel stop …”)
With respect to claim 1, Tezuka Daiki differs from the claimed invention in that is does not explicitly disclose:
the retaining structure is a retaining wall
obtaining ground data during the backing process of the vehicle, and sequentially performing ground determination and ground elimination on the ground data to obtain non-ground point cloud data; and
obtaining distance information between a rear end of the vehicle and the retaining wall and integrity data of the retaining wall by calculation according to the finally processed data of the retaining structure and the non-ground point cloud data
With respect to claim 1, Kumar et al discloses:
the retaining structure is a retaining wall (column 15, lines 35-53 state, “The sensed object information refers to sensed information regarding objects external to the vehicle. Examples include … curbs …walls (height and spatial locations), barricades (height and spatial locations), and the like.” Reference 1002 of Tezuka Daiki may be considered to serve as a curb or a barricade. Although Tezuka Daiki does not disclose a “wall”, one of ordinary skill in the art would recognize a wall, in view of Kumar’s teachings, to serve as an obvious and equivalent replacement to the wheel stop of Tezuka Daiki, since both serve the same function of preventing the vehicle from backing up any further.)
obtaining ground data during the backing process of the vehicle, and sequentially performing ground determination and ground elimination on the ground data to obtain non-ground point cloud data (figure 9, references 925 and 930; column 24, lines 42-46 state, “this object detection pipeline can comprise a set of ground surface estimation instructions 810 that perform ground segmentation as will be described in detail below and identifies ground and non-ground spatial points from the LiDAR point cloud 805.” Column 26, lines 39-52 state, “Minimum filtering can then be performed … performing minimum filtering on the spatial points of the maximum height map can comprise estimating 925 a local ground heigh value at each spatial point … Each spatial point can then be classified 930 by the navigation system 302 as a ground point or a non-ground point based on the minimum filtering of each spatial point.”)
obtaining distance information between a rear end of the vehicle and the retaining wall and integrity data of the retaining wall by calculation according to the finally processed data of the retaining structure and the non-ground point cloud data (obvious in view of combination; Tezuka Daiki discloses measuring distance to rear wheel stop (paragraph 0006) and extracting point cloud data (paragraphs 0060 and 0069). Kumar discloses distinguishing point cloud data for both ground and non-ground. It also discloses distance determination (column 8, lines 7-9 state, “The LIDAR sensor/system 320 may include one or more components configured to measure distances to targets using laser illumination …”)
With respect to claim 1, it would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to incorporate the teachings of Kumar et al into the invention of Tezuka Daiki. The motivation for the skilled artisan in doing so is to gain the benefit of greater accuracy and variability in the type of objects an autonomous vehicle can detect and the ability in which to detect them.
With respect to claim 2, Tezuka Daiki, as modified, discloses:
wherein the original data include attitude information and motion state information of the vehicle and point cloud data related to the retaining wall behind the automatic driving vehicle (obvious in view of combination; see Tezuka Daiki figures 1-3, 7-8, and 10; the variables that are measured and considered broadly include both attitude information and motion state information; see also paragraph 0048, which states, “as the dump truck 1 approaches the wheel stop 1002, the second scan surface 22 moves toward the upper end of the inclined surface 1002a.”; See also paragraph 0060 and 0069 for point cloud teachings. Kumar also teaches position (i.e. attitude) and motion detection (column 4, lines 5-8; column 12, lines 22-29), as well as point cloud (abstract; column 24, lines 32-67).)
With respect to claim 4, Tezuka Daiki, as modified, discloses:
wherein sequentially performing the ground determination and the ground elimination on the ground data to obtain the non-ground point cloud data comprises: (obvious in view of combination, particularly in view of Kumar’s non-ground point teachings)
sequentially obtaining geometric features of an area where projections on a ground of points in the point cloud are located according to the ground data, and determining whether the points are ground points according to the geometric features of the area; if so, filtering out of the points; otherwise, reserving the points, thus obtaining point cloud data of non-ground point information (obvious in view of combination, particularly in view of Kumar’s non-ground point teachings, as discussed above; obtaining geometric features is suggested by the use of LiDAR)
constructing and outputting the non-ground point cloud data according to the point cloud data of the non-ground point information (obvious in view of combination, particularly in view of Kumar’s non-ground point teachings, as discussed above; obtaining geometric features is suggested by the use of LiDAR)
With respect to claim 5, Tezuka Daiki, as modified, discloses:
wherein obtaining the distance information between the rear end of the vehicle and the retaining wall and the integrity data of the retaining wall by calculation according to the finally processed data of the retaining wall and the non-ground point cloud data comprises: (obvious in view of combination, particularly in view of Kumar’s non-ground point teachings, as discussed above; The claimed limitation of “converting the non-ground point cloud data into a well-ordered set …” is broadly construed to be anticipated by Kumar’s teachings of “classifying each spatial point as a ground point or a non-ground point …”)
converting the non-ground point cloud data into a well-ordered set according to a preset well-ordered relationship, and creating necessary geometric elements according to the finally processed data of the retaining wall and size parameters of the vehicle (obvious in view of combination, particularly in view of Kumar’s non-ground point teachings, as discussed above; The claimed limitation of “converting the non-ground point cloud data into a well-ordered set …” is broadly construed to be anticipated by Kumar’s teachings of “classifying each spatial point as a ground point or a non-ground point …”)
calculating the distance information between the rear end of the vehicle and the retaining wall according to the well-ordered set and the necessary geometric elements (obvious in view of combination, particularly in view of Kumar’s non-ground point teachings, as discussed above; The claimed limitation of “converting the non-ground point cloud data into a well-ordered set …” is broadly construed to be anticipated by Kumar’s teachings of “classifying each spatial point as a ground point or a non-ground point …”)
determining the integrity data of the retaining wall behind the vehicle according to the well-ordered set, the necessary geometric elements and the distance information between the rear end of the vehicle and the retaining wall (obvious in view of combination, particularly in view of Kumar’s non-ground point teachings, as discussed above; The claimed limitation of “converting the non-ground point cloud data into a well-ordered set …” is broadly construed to be anticipated by Kumar’s teachings of “classifying each spatial point as a ground point or a non-ground point …”)
Claim 10 represents a system claim variation of claim 1. It is rejected for similar reasons. Please note that Tezuka Daiki discloses, “may be implemented in a microcontroller device including a central processing unit, memory device, input/output circuit, and communication circuit, and may be configured by a combination of hardware and software that realizes the functions of each device, or each device may be configured by a processing circuit.” (paragraph 0043). This anticipates the generic modules disclosed in claim 10.
Allowable Subject Matter
Claims 3 and 6-9 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.
Claim 3, discloses the following limitations, which when considered together as a whole, were not found, taught, disclosed, or suggested in the prior art:
determining whether a distance from a coordinate of a point in point cloud data to a coordinate origin is less than a preset distance; if so, determining the point indicated by the coordinate as an invalid point that needs to be filtered out; otherwise, determining the point indicated by the coordinate as a valid point that needs to be reserved
performing dilation transformation on coordinates of data obtained after invalid points are filtered out
performing orthogonal transformation on the data subjected to the dilation transformation to transform a reference system of the data subjected to the dilation transformation from a sensor coordinate system to a vehicle coordinate system
determining, according to size parameters of the vehicle, whether a coordinate of a point after the orthogonal transformation belongs to a vehicle body; if so, determining the point indicated by the coordinate as an invalid point that needs to be filtered out; otherwise, determining the point indicated by the coordinate is a valid point that needs to be reserved; and
determining whether a point left after invalid points belonging to the vehicle body are filtered out is a noisy point according to a change in attribute of the point; if so, filtering out of the noisy point, thus obtaining the final processed data of the retaining wall
Art was found to teach general disclosure of some of the claimed elements. For example, CN112801022A (mentioned in the citation of pertinent prior art section below) states, “The method converts 64-line LiDAR point cloud into two-dimensional grid data, uses and dilation operations to ensure that the overall outline of the obstacle data remains unchanged, the calculates the outline of each obstacle …” However, the applicant could not find proper teachings to account for the detailed whole of all of the above claimed limitations, when considered together, nor could the examiner find proper motivation to combine piecemeal teachings of some of the individual elements mentioned, such as general dilation or orthogonal transformations.
Claim 6 discloses, “The method for detecting the retaining wall suitable for the automatic driving vehicle according to claim 5, wherein the well-ordered relationship is expressed as …” The specific claimed equation that defines the claimed well-ordered relationship was not found, taught, suggested, or disclosed in the prior art, particularly not in the context of all the disclosure in claim 5 (and the claims that preceded it).
Claims 7-9 depend on claim 6 and are also objected to as being allowable, as a result of their dependency.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
You (CN112801022A) discloses a method for rapid detection and updating of road boundaries in unmanned mining truck operation areas. Both original foreign document and machine translation for included.
Yang, Z.; Pingshu, G.; Jingyi, Xu; Tao, Z.; and Qian, Z. – “Lidar-based Vehicle Target Recognition”; Proceedings of the 2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI), Hangzhou, China, December 18-20, 2020.
Sun, P.; Zhao, X.; Zhigang, X.; Wang, R.; and Min H. – “A 3D LiDAR Data-Based Dedicated Road Boundary Detection Algorithm for Autonomous Vehicles”; IEEE Access, Volume 7, 2019, pages 29623 – 29638.
Zhang et al (US PgPub 20210004021) discloses generating training data for deep learning models for building high definition maps.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LEONARD S LIANG whose telephone number is (571)272-2148. The examiner can normally be reached M-F 10:00 AM - 7 PM.
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/LEONARD S LIANG/Examiner, Art Unit 2857 08/08/26
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