DETAILED ACTION
This action is in response to the initial filing filed on October 10, 2024 Claims 1-20 havebeen examined in this application.
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
No Information Disclosure Statement (IDS) has been filed for this application.
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e. an abstract idea) without significantly more.
Step 1: Claims 1-14, and 20 are drawn to a method and claims 15-19 are drawn to a device (i.e., a manufacture). As such, claims 1-20 are drawn to one of the statutory categories of invention (Step 1: YES).
Under Step 2A Prong 1, the claims are analyzed to determine whether the claims recite any judicial exceptions including certain groupings of abstract ideas (i.e., mathematical concepts, certain methods of organizing human activity such as a fundamental economic practice, or mental processes).
Claims 1, and 15, recite a path planning method for putting on the green, applied to a spatial multi-dimensional scanning device, comprising: scanning a planned green to obtain a spatial multi-dimensional information map of the green; analyzing the spatial multi-dimensional information map to obtain an elevation information of the green; performing a target detection on the spatial multi-dimensional information map to determine positions of a golf ball and a hole in the spatial multi-dimensional information map; and generating a batting path information according to the elevation information and positions of the golf ball and hole, to complete a path planning for the green according to the batting path information. If claim limitations, under their broadest reasonable interpretation, include a mental process and/or certain methods of organizing human activity, the limitations fall under the abstract ideas judicial exception and therefore recite ineligible subject matter. Accordingly, claims 1, and 15 recite abstract ideas.
Representative Claim 1: A path planning method for putting on the green, applied to a spatial multi-dimensional scanning device, comprising: scanning a planned green to obtain a spatial multi-dimensional information map of the green; analyzing the spatial multi-dimensional information map to obtain an elevation information of the green; performing a target detection on the spatial multi-dimensional information map to determine positions of a golf ball and a hole in the spatial multi-dimensional information map; and generating a batting path information according to the elevation information and positions of the golf ball and hole, to complete a path planning for the green according to the batting path information.
Representative Claim 15: A spatial multi-dimensional scanning device, wherein the spatial multi-dimensional scanning device comprises a memory and a processor; the memory is configured to store a computer program; the processor is configured to execute the computer program and implement a path planning method for putting on the green, wherein the method comprises: scanning a planned green to obtain a spatial multi-dimensional information map of the green; analyzing the spatial multi-dimensional information map to obtain an elevation information of the green; performing a target detection on the spatial multi-dimensional information map to determine positions of a golf ball and a hole in the spatial multi-dimensional information map; and generating a batting path information according to the elevation information and positions of the golf ball and hole, to complete a path planning for the green according to the batting path information.
(Examiner notes: The underlined claim terms above are interpreted as additional elements beyond the abstract idea and are further analyzed under Step 2A - Prong Two)
The additional elements are instructions for applying the judicial exceptions with a generic computing device as, under their broadest reasonable interpretation, the additional elements of a scanning device, and processing circuitry are generic computer components for performing the above method, per MPEP 2106.05(f). Under their broadest reasonable interpretation, the additional elements are generic components of a computing device used to apply the abstract idea.
Under their broadest reasonable interpretation, the recited steps of a path planning method for putting on the green: scanning a green, analyzing the scanned map, performing target detection on the scanned map; and generating a batting path (i.e., one or more concepts performed in the human mind, such as one or more observations, evaluations, judgments, opinions), then it also falls within the “Mental Processes” subject matter grouping of abstract ideas. The recited steps are a simulation that applies an abstract idea, specifically mental processes (observation (scanning a green, and performing target detection)) and/or evaluation (analyzing the scanned map, and generating a batting path)). If claim limitations, under their broadest reasonable interpretation, include a mental process and/or certain methods of organizing human activity (CMOHA), the limitations fall under the abstract ideas judicial exception and therefore recite ineligible subject matter. Accordingly, claims 1, and 15 recite abstract ideas.
Dependent Claims 4-14, and 18-201 further narrow the abstract ideas of stopping a game, displaying content, analyzing responses, enabling multiple users to participate in a game, customizing text, and narrating gameplay (i.e., one or more concepts performed in the human mind, such as one or more observations, evaluations, judgments, opinions), then it also falls within the “Mental Processes” and is an abstract idea and then it also falls within the “Organizing Human Processes” subject matter grouping of abstract ideas and then also falls within the “Organizing Human Processes” subject matter grouping of abstract ideas.
Independent claim(s) 1, and 15 recite/describe nearly identical steps (and therefore also recite limitations that fall within this subject matter grouping of abstract ideas), and this/these claim(s) is/are therefore determined to recite an abstract idea under the same analysis.
As such, the Examiner concludes that claims 1, and 15 recite an abstract idea (Step 2A – Prong One: YES).
Under Step 2A Prong 2 the claims are analyzed to determine whether the claims recite additional elements that integrate the judicial exception into a practical application.
Step 2A - Prong Two: In prong two of step 2A, an evaluation is made whether a claim recites any additional element, or combination of additional elements, that integrate the exception into a practical application of that exception. An “addition element” is an element that is recited in the claim in addition to (beyond) the judicial exception (i.e., an element/limitation that sets forth an abstract idea is not an additional element). The phrase “integration into a practical application” is defined as requiring an additional element or a combination of additional elements in the claim to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that it is more than a drafting effort designed to monopolize the exception.
The requirement to execute the claimed steps/functions using “scanning a green”, “analyzing the scanned map”, “performing target detection on the scanned map”, and “generating a batting path” etc. (Claims 1, and 15) are equivalent to adding the words “apply it” on a generic computer and/or mere instructions to implement the abstract idea on a generic computer.
Similarly, the limitations of applying “scanning a green”, “analyzing the scanned map”, “performing target detection on the scanned map”, and “generating a batting path” etc. Independent Claim(s) 1, and 15, and dependent claims 4-14, and 18-20 are recited at a high level of generality and amount to no more than mere instructions to apply the exception using generic computer components in a vehicle. This/these limitation(s) do/does not impose any meaningful limits on practicing the abstract idea, and therefore do/does not integrate the abstract idea into a practical application (see MPEP 2106.05(f)).
Further, the additional limitations beyond the abstract idea identified above, serves merely to generally link the use of the judicial exception to a particular technological environment or field of use. Specifically, it/they serve(s) to limit the application of the abstract idea to computerized environments (e.g., scanning a green, analyzing the scanned map, performing target detection on the scanned map, and generating a batting path etc.). This/these limitation(s) do/does not impose any meaningful limits on practicing the abstract idea, and therefore do/does not integrate the abstract idea into a practical application (see MPEP 2106.05(h)).
The recited additional element(s) of obtaining structured and visible light images, obtaining distance information, constructing an elevation model, obtaining slope information, generating multiple candidate paths, updating path information after a ball moves, and extracting features of a golf ball and hole (Claim(s) 1, and 15), additionally and/or alternatively simply append insignificant extra-solution activity to the judicial exception, (e.g., mere pre-solution activity, such as data gathering, in conjunction with an abstract idea). This/these limitation(s) do/does not impose any meaningful limits on practicing the abstract idea, and therefore do/does not integrate the abstract idea into a practical application. (See MPEP 2106.05(g)).
Dependent claims 4-14, 18-20 fail to include any additional elements. In other words, each of the limitations/elements recited in respective dependent claims is/are further part of the abstract idea as identified by the Examiner for each respective dependent claim (i.e. they are part of the abstract idea recited in each respective claim).
The Examiner has therefore determined that the additional elements, or combination of additional elements, do not integrate the abstract idea into a practical application. Accordingly, the claim(s) is/are directed to an abstract idea (Step 2A – Prong two: NO).
Step 2B: In step 2B, the claims are analyzed to determine whether any additional element, or combination of additional elements, is/are sufficient to ensure that the claims amount to significantly more than the judicial exception. This analysis is also termed a search for an "inventive concept." An "inventive concept" is furnished by an element or combination of elements that is recited in the claim in addition to (beyond) the judicial exception, and is sufficient to ensure that the claim as a whole amounts to significantly more than the judicial exception itself.
As discussed above in “Step 2A – Prong 2”, the identified additional elements in independent claim(s) 1, and 15, and dependent claims 4-14, and 18-20 are equivalent to adding the words “apply it” on a generic computer, and/or generally link the use of the judicial exception to a particular technological environment or field of use. Therefore, the claims as a whole do not amount to significantly more than the judicial exception itself.
The recited additional element(s) of scanning a green, analyzing the scanned map, performing target detection on the scanned map, and generating a batting path (Claim(s) 1, and 15), additionally and/or alternatively simply append insignificant extra-solution activity to the judicial exception, (e.g., mere pre-solution activity, such as data gathering, in conjunction with an abstract idea) i.e. selecting users (i.e. using a user interface) is similar to “Receiving or transmitting data over a network, e.g., using the Internet to gather data”, is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here) (See MPEP 2106.05(d) (II)).
This conclusion is based on a factual determination. Applicant’s own disclosure at paragraphs [0016], and [0094] acknowledges that “In the second aspect, the present disclosure provides a spatial multi-dimensional scanning device, includes: a memory and a processor; the memory is configured to store a computer program; the processor is configured to execute the computer program and implement the above any path planning method”, and “In an embodiment, the processor is configured to invoke the computer program stored in the memory to perform the following steps: scanning a planned green to obtain a spatial multi-dimensional information map of the green; analyzing the spatial multi-dimensional information map to obtain an elevation information of the green; performing a target detection on the spatial multi-dimensional information map to determine positions of a golf ball and a hole in the spatial multi-dimensional information map; and generating a batting path information according to the elevation information and positions of the golf ball and hole, to complete a path planning for the green according to the batting path information” (i.e. conventional nature of using a computer and/or computer program). This additional element therefore does not ensure the claim amounts to significantly more than the abstract idea.
Viewing the additional limitations in combination also shows that they fail to ensure the claims amount to significantly more than the abstract idea. When considered as an ordered combination, the additional components of the claims add nothing that is not already present when considered separately, and thus simply append the abstract idea with words equivalent to “apply it” on a generic computer and/or mere instructions to implement the abstract idea on a generic computer or/and append the abstract idea with insignificant extra solution activity associated with the implementation of the judicial exception, and/or simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception.
The dependent claims 4-14, 16-19, and 20 are dependent from claims 1, and 15 and include all the limitations of the independent claims, but fail to include any additional elements. In other words, each of the limitations/elements recited in respective independent claims is/are further part of the abstract idea as identified by the Examiner for each respective dependent claim (i.e. they are part of the abstract idea recited in each respective claim). Therefore, the dependent claims recite the same abstract idea. The limitations of the dependent claims fail to amount to significantly more than the judicial exception. For example:
The limitations of claims 4, 5, 6, 7, 8, 9, 11, 12, 14, and 19 recite clarifications of obtaining structured and visible light images, obtaining distance information, constructing an elevation model, obtaining slope information, generating multiple candidate paths, updating path information after a ball moves, and extracting features of a golf ball and hole. Such clarifications, under their broadest reasonable interpretation, are merely defining/selecting a type of data to be manipulated which, per MPEP 2106.05(g), is insignificant extra-solution activity. Therefore, the limitations fail to provide any teaching that integrates the judicial exceptions into a practical application or amount to significantly more than the judicial exception. For this reason, the analysis performed on the independent claims is also applicable on these claims.
The limitations of claim 10, 13, and 20 recite clarifications of scanning and processing data, applying an algorithm to the processed data, and performing the analysis and data processing utilizing a computer program. The limitations are further instructions for applying the judicial exceptions with a generic computing device/interface acting as an intermediary for performing the abstract ideas of scanning a green, analyzing the scanned map, performing target detection on the scanned map, and generating a batting path, see MPEP 2106.05(f). Therefore, the limitations fail to provide any teaching that integrates the judicial exceptions into a practical application or amount to significantly more than the judicial exception. For this reason, the analysis performed on the independent claims is also applicable on these claims.
The Examiner has therefore determined that no additional element, or combination of additional claims elements is/are sufficient to ensure the claim(s) amount to significantly more than the abstract idea identified above (Step 2B: NO).
Therefore, claims 1, 4-15, and 19-20 are not eligible subject matter under 35 USC 101.
Claim Rejections – USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 11, 12, 15, and 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Barkley et al. (US 8,449,409 B1).
Regarding Claim 1, Barkley discloses a path planning method for putting on the green, applied to a spatial multi-dimensional scanning device (Col. 2 Lines 15-50 The distance sensor (multi-dimensional scanning) 66 receives a trigger 73 from the processor 67. and provides a plurality of distance measurements 72 to the processor 67. This plurality of distance measurements 72 typically consists of thousands of distance measurements between the distance sensor 66 and corresponding points on a surface of interest, which in this case is a putting green… The processor 67 uses the received angular orientation 74 and plurality of distance measurements 72 to compute the topography (spatial multi-dimensional measurements) of the putting green, and provide user-specified graphical putting aid (path planning for putting) data 76 to the display 65/71), comprising:
scanning a planned green to obtain a spatial multi-dimensional information map of the green (Col. 2 Lines 29-32 This plurality of distance measurements 72 typically consists of thousands of distance measurements between the distance sensor 66 and corresponding points on a surface of interest, which in this case is a putting green, Col. 2 Lines 34-36 The processor 67 uses the received angular orientation 74 and plurality of distance measurements 72 to compute the topography (multi-dimensional information map) of the putting green, Col. 2 Lines 55-61 The processor 67 then waits upon a trigger 78 from button 60, which indicates that a user has requested graphical putting aid of a putting green. Upon receipt of this trigger 78, the processor 67 retrieves a plurality of distance measurements 72 from the distance sensor 66, and an angular orientation 74 of the distance sensor 66 from the tilt sensor 68, Col. 3 Lines 25-26 This is done for the entire plurality of distance measurements 72, thus computing the topography of the putting surface 58);
analyzing the spatial multi-dimensional information map to obtain an elevation information of the green (Col. 3 Lines 8-13 Each distance measurement is multiplied by the Cosine of its corresponding numerical constant (angle), producing a number which represents the vertical distance between the elevation of the distance sensor 66 and the elevation of the corresponding point on the putting surface 58 (analyzing spatial multi-dimensional information map), Col. 3 Line 17-21 After the vertical distances described above have been computed, the elevation with respect to the lowest point within the distance sensor's 66 field-of-view is computed by subtracting each vertical distance from the maximum vertical distance (elevation info));
performing a target detection on the spatial multi-dimensional information map to determine positions of a golf ball and a hole in the spatial multi-dimensional information map (Col. 3 Lines 41-43 First, the golf ball's 80 and hole's 84 locations are determined with a simple image processing algorithm (target detection), Col. 3 Lines 48-52 Changes in elevation and color within these marked regions on the display 65/71 indicate the locations of the golf ball 80 and hole 84. With these locations, a rough estimate of a successful putt is computed, and the calculated point at which the golf ball 80 stops is temporarily saved); and
generating a batting path information according to the elevation information and positions of the golf ball and hole, to complete a path planning for the green according to the batting path information (Col. 3 Lines 40-41 A successful putt trajectory 83 (batting path) is computed using basic kinematics, Col. 3 Lines 50-52 With these locations, a rough estimate of a successful putt is computed (batting path information), and the calculated point at which the golf ball 80 stops is temporarily saved, Col. 3 Lines 54-55 This continues until the putt successfully arrives at the targeted hole 84, Col. 3 Lines 60-64 After the color frame has been constructed, the processor 67 transmits this color frame, or graphical putting aid data 76, to the display 65/71, thus fulfilling the request 78 of the user for graphical putting aid (completing a path planning for the green)).
Regarding Claim 11, Barkley discloses wherein the performing a target detection on the spatial multi-dimensional information map to determine positions of a golf ball and a hole in the spatial multi-dimensional information map comprises:
segmenting the spatial multi-dimensional information map into different areas to identify specific targets (Col. 3 Lines 40-50 In the preferred embodiment, marked regions on the display 65/71 indicate areas to place the golf ball 80 and hole 84 when aiming the device 64. This serves to fully utilize the resolution of the distance sensor 66, and eases the process of locating the golf ball 80 and hole 84);
extracting features of a golf ball and a hole (Col. 3 Lines 45-50 Changes in elevation and color within these marked regions on the display 65/71 indicate the locations of the golf ball 80 and hole 84); and
identifying the golf ball and hole, according to the features, and determining positions of the golf ball and hole (Col. 3 Lines 40-45 First, the golf ball's 80 and hole's 84 locations are determined with a simple image processing algorithm).
Regarding Claim 12, Barkley discloses The method according to claim 11, wherein the features comprise a color feature and a shape feature (Col. 3 Lines 45-50 Changes in elevation and color (color feature) within these marked regions on the display 65/71 indicate the locations of the golf ball 80 and hole 84; Col. 3 Lines 40-45 First, the golf ball's 80 and hole's 84 locations are determined with a simple image processing algorithm, Col. 4 Lines 35-40 Viable methods for a distance sensing unit could be through the use of stereo triangulation, sheet of light triangulation (shape feature), time-of-flight camera, LIDAR, structured light 3D scanner, interferometry, or many other distance sensing methodologies);
the identifying the golf ball and hole according to the features comprises:
performing a preliminary detection in the spatial multi-dimensional information map to obtain color regions according to the color feature of the golf ball and hole (Col. 3 Lines 40-50 In the preferred embodiment, marked regions on the display 65/71 indicate areas to place the golf ball 80 and hole 84 when aiming the device 64… Changes in elevation and color (color regions) within these marked regions on the display 65/71 indicate the locations of the golf ball 80 and hole 84); and
identifying the ball and hole from the color regions according to the shape feature of the golf ball and hole (Col. 3 Lines 40-45 First, the golf ball's 80 and hole's 84 locations are determined with a simple image processing algorithm, Col. 4 Lines 35-40 Viable methods for a distance sensing unit could be through the use of stereo triangulation, sheet of light triangulation (shape feature), time-of-flight camera, LIDAR, structured light 3D scanner, interferometry, or many other distance sensing methodologies).
Regarding Claim 15, Barkley discloses A spatial multi-dimensional scanning device (Col. 2 Lines 61-65 Upon receipt of the angular orientation 74, the processor 67 retrieves corresponding predetermined numerical constants from memory on-board the processor 67 (numerical constants are gathered through a calibration process explained later in this section)),
wherein the spatial multi-dimensional scanning device comprises a memory and a processor (Col. 5 Lines 18-23 The device of claim 2 further comprising a memory storage element for storing predetermined numerical constants; whereby said processor uses said predetermined numerical constants);
the memory is configured to store a computer program (Col. 4 Lines 47-52 The processor 67 can be any circuit which performs the required computations. This circuit could be built around a micro-controller (inherently capable of storing a computer program), FPGA, or many other components, The user interface 70 could be any combination of buttons, switches, dials, keys, touchscreens, or any other means through which a user communicates to the present invention);
the processor is configured to execute the computer program and implement a path planning method for putting on the green (Col. 2 Lines 15-50 The distance sensor (multi-dimensional scanning) 66 receives a trigger 73 from the processor 67. and provides a plurality of distance measurements 72 to the processor 67. This plurality of distance measurements 72 typically consists of thousands of distance measurements between the distance sensor 66 and corresponding points on a surface of interest, which in this case is a putting green… The processor 67 uses the received angular orientation 74 and plurality of distance measurements 72 to compute the topography (spatial multi-dimensional measurements) of the putting green, and provide user-specified graphical putting aid (path planning for putting) data 76 to the display 65/71), wherein the method comprises:
scanning a planned green to obtain a spatial multi-dimensional information map of the green (Col. 2 Lines 29-32 This plurality of distance measurements 72 typically consists of thousands of distance measurements between the distance sensor 66 and corresponding points on a surface of interest, which in this case is a putting green, Col. 2 Lines 34-36 The processor 67 uses the received angular orientation 74 and plurality of distance measurements 72 to compute the topography of the putting green, Col. 2 Lines 55-61 The processor 67 then waits upon a trigger 78 from button 60, which indicates that a user has requested graphical putting aid of a putting green. Upon receipt of this trigger 78, the processor 67 retrieves a plurality of distance measurements 72 from the distance sensor 66, and an angular orientation 74 of the distance sensor 66 from the tilt sensor 68, Col. 3 Lines 25-26 This is done for the entire plurality of distance measurements 72, thus computing the topography of the putting Surface 58);
analyzing the spatial multi-dimensional information map to obtain an elevation information of the green (Col. 3 Lines 8-13 Each distance measurement is multiplied by the Cosine of its corresponding numerical constant (angle), producing a number which represents the vertical distance between the elevation of the distance sensor 66 and the elevation of the corresponding point on the putting surface 58; Col. 3 Line 17-21 After the vertical distances described above have been computed, the elevation with respect to the lowest point within the distance sensor's 66 field-of-view is computed by subtracting each vertical distance from the maximum vertical distance);
performing a target detection on the spatial multi-dimensional information map to determine positions of a golf ball and a hole in the spatial multi-dimensional information map (Col. 3 Lines 41-43 First, the golf ball's 80 and hole's 84 locations are determined with a simple image processing algorithm (target detection), Col. 3 Lines 48-52 Changes in elevation and color within these marked regions on the display 65/71 indicate the locations of the golf ball 80 and hole 84. With these locations, a rough estimate of a successful putt is computed, and the calculated point at which the golf ball 80 stops is temporarily saved); and
generating a batting path information according to the elevation information and positions of the golf ball and hole, to complete a path planning for the green according to the batting path information (Col. 3 Lines 40-41 A successful putt trajectory 83 (generating a batting/putting path information) is computed using basic kinematics, Col. 3 Lines 50-52 With these locations, a rough estimate of a successful putt is computed, and the calculated point at which the golf ball 80 stops is temporarily saved, Col. 3 Lines 54-55 This continues until the putt successfully arrives at the targeted hole 84, Col. 3 Lines 60-64 After the color frame has been constructed, the processor 67 transmits this color frame, or graphical putting aid data 76, to the display 65/71, thus fulfilling the request 78 of the user for graphical putting aid).
Regarding Claim 20, Barkley teaches a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, the computer program comprises program instructions, when the program instructions are executed by a processor, the processor performs a path planning method for putting on the green according to claim 1 (Col. 5 Lines 18-23 The device of claim 2 further comprising a memory storage element for storing predetermined numerical constants; whereby said processor uses said predetermined numerical constants; Col. 2 Lines 61-65 Upon receipt of the angular orientation 74, the processor 67 retrieves corresponding predetermined numerical constants from memory on-board the processor 67 (numerical constants are gathered through a calibration process explained later in this section); Col. 4 Lines 47-49 The processor 67 can be any circuit which performs the required computations. This circuit could be built around a micro-controller, FPGA, or many other components (functionally analogous to a computer-readable storage medium)).
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.
Claims 2, 3, 10, 16, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Barkley et al. (US 8,449,409 B1), in view of Kiraly (US 2004/0032970 A1).
Regarding Claim 2, Barkley discloses wherein the spatial multi-dimensional scanning device comprises a structured light acquisition module and a visible light acquisition module (Col. 4 Lines 35-39 Viable methods for a distance sensing unit could be through the use of stereo triangulation, sheet of light triangulation, time-of-flight camera, LIDAR, structured light 3D scanner, interferometry, or many other distance sensing methodologies (various examples of structured light acquisition modules), Col. 3 Lines 48-50 Changes in elevation and color within these marked regions on the display 65/71 indicate the locations of the golf ball 80 and hole 84, Col. 3 Lines 33-36 Elevation shading 85 is applied by scaling color data to the computed topographical data. For example, pixels are colored from dark green to light yellow as elevation rises);
the scanning a planned green to obtain a spatial multi-dimensional information map of the green comprises:
obtaining a light image of the green scanned and collected by the light acquisition module (Col. 2 Lines 26-29 The distance sensor 66 receives a trigger 73 from the processor 67 and provides a plurality of distance measurements 72 to the processor 67, Col. 4 Lines 28-30 The display 65/71 could be any means of exhibiting visual aid to a user);
obtaining a visible light image of the green scanned and collected by the visible light acquisition module (Col. 4 Lines 28-30 The display 65/71 could be any means of exhibiting visual aid to a user); and
generating the spatial multi-dimensional information map according to the structured light image and the visible light image (Col. 3 Lines 27-29 Once topographical data has been computed, the processor 67 constructs a color frame comprising any user-specified graphical putting aid, Col. 3 Lines 60-64 After the color frame has been constructed, the processor 67 transmits this color frame, or graphical putting aid data 76, to the display 65/71, thus fulfilling the request 78 of the user for graphical putting aid).
However, Barkley is not relied upon disclosing obtaining a structured light image of the green scanned and collected by the structured light acquisition module.
Kiraly teaches obtaining a structured light image of the green scanned and collected by the structured light acquisition module ([0085] The system captures multiple images of the ball 206 during its flight, with one or more images taken while the ball is illuminated by the structured light source 202. Assuming the camera system 152 is calibrated to world coordinates, the system 152 computes a 3D vector for a line from the camera 152 which intersects the ball 206 at the point of illumination by the structured light source 202).
Barkley and Kiraly are both considered to be analogous to the claimed invention, because they are in the same field of golf aids with ball trajectory analysis. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filling date of the applicant’s invention for modifying the a path planning method for putting on the green, applied to a spatial multi-dimensional scanning device, as disclosed by Barkley, further including obtaining a structured light image of the green scanned and collected by the structured light acquisition module, as taught by Kiraly for the purpose of computing a 3D vector line from the camera to the ball, while also using the position and directional orientation of the light source relative to the camera to determine the position and trajectory of the ball (Kiraly, [0085]).
Regarding Claim 3, Barkley discloses wherein the spatial multi-dimensional scanning device further comprises a ranging module (Col. 4 Lines 39-40 The distance sensor 66 could be any device that measures distance from one point to the next);
the generating the spatial multi-dimensional information map according to the structured light image and the visible light image comprises:
obtaining a distance information of the green scanned and collected by the ranging module (Col. 2 Lines 50-61 the processor 67 retrieves a plurality of distance measurements 72 from the distance sensor 66, and an angular orientation 74 of the distance sensor 66 from the tilt sensor 68); and
generating the spatial multi-dimensional information map (Col. 3 Lines 2-4 The processor 67 then uses the received plurality of distance measurements 72 and numerical constants (angles) to compute the topography (multidimensional information map) of the putting green, Col. 3 Lines 27-29 Once topographical data has been computed, the processor 67 constructs a color frame comprising any user-specified graphical putting aid).
However, Barkley is not relied upon disclosing generating the spatial multi-dimensional information map according to the distance information, structured light image and visible light image.
Kiraly teaches generating the spatial multi-dimensional information map according to the distance information, structured light image and visible light image ([0085] The system captures multiple images of the ball 206 during its flight, with one or more images taken while the ball is illuminated by the structured light source 202. Assuming the camera system 152 is calibrated to world coordinates, the system 152 computes a 3D vector for a line from the camera 152 which intersects the ball 206 at the point of illumination by the structured light source 202, [0109] Since the correlation is performed in the 2D-image plane the reference ball image B1 must be converted from the 3D world coordinate system to the 2D-image plane (multidimensional information map). This is accomplished using the 3D World vector that originates from the camera and passes through the center of each ball).
Regarding Claim 10, Barkley discloses wherein the scanning a planned green to obtain a spatial multi-dimensional information map of the green comprises:
scanning a planned green through the spatial multi-dimensional scanning device (Col. 2 Lines 29-32 This plurality of distance measurements 72 typically consists of thousands of distance measurements between the distance sensor 66 and corresponding points on a surface of interest, which in this case is a putting green (a planned green), Col. 2 Lines 34-36 The processor 67 uses the received angular orientation 74 and plurality of distance measurements 72 to compute the topography (multi-dimensional) of the putting green, Col. 2 Lines 55-61 The processor 67 then waits upon a trigger 78 from button 60, which indicates that a user has requested graphical putting aid of a putting green. Upon receipt of this trigger 78, the processor 67 retrieves a plurality of distance measurements 72 from the distance sensor 66 (scanning), and an angular orientation 74 of the distance sensor 66 from the tilt sensor 68, Col. 3 Lines 25-26 This is done for the entire plurality of distance measurements 72, thus computing the topography of the putting surface 58); and
converting the processed data into a spatial multi-dimensional information map of the green (Col. 3 Lines 25-30 This is done for the entire plurality of distance measurements 72, thus computing the topography (spatial multi-dimensional information map) of the putting surface 58. Once topographical data has been computed (converting the processed data), the processor 67 constructs a color frame comprising any user-specified graphical putting aid).
However, Barkley is not relied upon disclosing wherein the scanning a planned green to obtain a spatial multi-dimensional information map of the green comprises: performing preliminary processing to obtain a processed data.
Kiraly teaches wherein the scanning a planned green to obtain a spatial multi-dimensional information map of the green comprises:
performing preliminary processing to obtain a processed data ([0092] Therefore, prior to correlation, each ball image is prepared by performing glint removal and lighting normalization (data preprocessing)).
Regarding Claim 16, Barkley discloses wherein the spatial multi-dimensional scanning device comprises a structured light acquisition module and a visible light acquisition module (Col. 4 Lines 35-39 Viable methods for a distance sensing unit could be through the use of stereo triangulation, sheet of light triangulation, time-of-flight camera, LIDAR, structured light 3D scanner, interferometry, or many other distance sensing methodologies (various examples of structured light acquisition modules), Col. 3 Lines 48-50 Changes in elevation and color within these marked regions on the display 65/71 indicate the locations of the golf ball 80 and hole 84, Col. 3 Lines 33-36 Elevation shading 85 is applied by scaling color data to the computed topographical data. For example, pixels are colored from dark green to light yellow as elevation rises);
the scanning a planned green to obtain a spatial multi-dimensional information map of the green comprises:
obtaining a light image of the green scanned and collected by the light acquisition module (Col. 2 Lines 26-29 The distance sensor 66 receives a trigger 73 from the processor 67. and provides a plurality of distance measurements 72 to the processor 67);
obtaining a visible light image of the green scanned and collected by the visible light acquisition module (Col. 4 Lines 28-30 The display 65/71 could be any means of exhibiting visual aid to a user); and
generating the spatial multi-dimensional information map according to the structured light image and the visible light image (Col. 3 Lines 27-29 Once topographical data has been computed, the processor 67 constructs a color frame comprising any user-specified graphical putting aid, Col. 3 Lines 60-64 After the color frame has been constructed, the processor 67 transmits this color frame, or graphical putting aid data 76, to the display 65/71, thus fulfilling the request 78 of the user for graphical putting aid).
However, Barkley is not relied upon disclosing obtaining a structured light image of the green scanned and collected by the structured light acquisition module.
Kiraly teaches obtaining a structured light image of the green scanned and collected by the structured light acquisition module ([0085] The system captures multiple images of the ball 206 during its flight, with one or more images taken while the ball is illuminated by the structured light source 202. Assuming the camera system 152 is calibrated to world coordinates, the system 152 computes a 3D vector for a line from the camera 152 which intersects the ball 206 at the point of illumination by the structured light source 202).
Regarding Claim 17, Barkley discloses wherein the spatial multi-dimensional scanning device further comprises a ranging module (Col. 4 Lines 39-40 The distance sensor 66 could be any device that measures distance from one point to the next);
the generating the spatial multi-dimensional information map according to the structured light image and the visible light image comprises:
obtaining a distance information of the green scanned and collected by the ranging module (Col. 2 Lines 50-61 the processor 67 retrieves a plurality of distance measurements 72 from the distance sensor 66, and an angular orientation 74 of the distance sensor 66 from the tilt sensor 68); and
generating the spatial multi-dimensional information map (Col. 3 Lines 2-4 The processor 67 then uses the received plurality of distance measurements 72 and numerical constants (angles) to compute the topography of the putting green, Col. 3 Lines 27-29 Once topographical data has been computed, the processor 67 constructs a color frame comprising any user-specified graphical putting aid).
However, Barkley is not relied upon disclosing generating the spatial multi-dimensional information map according to the distance information, structured light image and visible light image.
Kiraly teaches generating the spatial multi-dimensional information map according to the distance information, structured light image and visible light image ([0085] The system captures multiple images of the ball 206 during its flight, with one or more images taken while the ball is illuminated by the structured light source 202. Assuming the camera system 152 is calibrated to world coordinates, the system 152 computes a 3D vector for a line from the camera 152 which intersects the ball 206 at the point of illumination by the structured light source 202, [0109] Since the correlation is performed in the 2D-image plane the reference ball image B1 must be converted from the 3D world coordinate system to the 2D-image plane (multidimensional information map). This is accomplished using the 3D World vector that originates from the camera and passes through the center of each ball).
Claims 4-8 and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Barkley et al. (US 8,449,409 B1), in view of Sweeney (US 2005/0101415 A1).
Regarding Claim 4, Barkley is not relied upon disclosing wherein the batting path information at least comprises an optimal batting path, the generating a batting path information according to the elevation information and positions of the golf ball and hole comprises: constructing a digital elevation model of the green according to the elevation information; setting the position of the golf ball as a starting point and the position of the hole as an end point in the digital elevation model; and generating the optimal batting path from the starting point to the end point in the digital elevation model according to a preset path planning algorithm.
Sweeney teaches wherein the batting path information at least comprises an optimal batting path ([0018] Calculating the putting information includes determining for a plurality of location coordinates on a putting green optimal trajectories corresponding to a desired capture velocity for a golf ball to move from said location coordinate to an end point), the generating a batting path information according to the elevation information and positions of the golf ball and hole comprises:
constructing a digital elevation model of the green according to the elevation information ([0038] The Survey readings of the perimeter and elevation are then converted into a digital terrain model (DTM) data file which can be read by commercially available geographic information system (GIS) software);
setting the position of the golf ball as a starting point and the position of the hole as an end point in the digital elevation model ([0042] Once the gradient components of the surface has been generated, a computer program may simulate the rolling of a golf ball on that surface using known equations of motion, thus allowing a variety of putt paths to be predicted (inherently, the golf ball is the starting point and the hole is the ending point for a batting/putting path)); and
generating the optimal batting path from the starting point to the end point in the digital elevation model according to a preset path planning algorithm ([0018] Calculating the putting information includes determining for a plurality of location coordinates on a putting green optimal trajectories corresponding to a desired capture velocity for a golf ball to move from said location coordinate to an end point, [0053] The process of calculating a successful putt trajectory given known values for green speed, capture speed, or starting and ending ball positions can be determined by using a number of non-linear solving techniques).
Barkley and Sweeney are both considered to be analogous to the claimed invention, because they are in the same field of golf aids. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filling date of the applicant’s invention for modifying the a path planning method for putting on the green, applied to a spatial multi-dimensional scanning device, as disclosed by Barkley, further including constructing a digital elevation model of the green according to the elevation information; setting the position of the golf ball as a starting point and the position of the hole as an end point in the digital elevation model; and generating the optimal batting path from the starting point to the end point in the digital elevation model according to a preset path planning algorithm, as taught by Sweeney for the purpose of aiding in putting by finding the optimal path and launch conditions, as well as determining breaks in greens (Sweeney, [0055]-[0056]).
Regarding Claim 5, Barkley is not relied upon disclosing wherein the batting path information further comprises a putting strength;
after the generating the optimal batting path from the starting point to the end point in the digital elevation model according to a preset path planning algorithm, the method further comprises:
obtaining a slope information and a friction coefficient corresponding to the optimal batting path in the digital elevation model; and
calculating the putting strength required for the golf ball to roll along the optimal batting path in the digital elevation model according to the slope information and friction coefficient.
Sweeney teaches wherein the batting path information further comprises a putting strength ([0072] calculating a putting parameter for propelling (putting strength) the golf ball from the start position to the target location based on a trajectory corresponding to a desired capture velocity of the ball, wherein the trajectory has a start point Substantially corresponding to the start position and an end point substantially corresponding to the target location. The putting parameters displayed may include an aim angle, an initial velocity);
after the generating the optimal batting path from the starting point to the end point in the digital elevation model according to a preset path planning algorithm, the method further comprises ([0011] The trajectories are determined by computing gradients between adjacent points of the three dimensional Surface model along each trajectory… Indicia indicative of a slope direction and slope magnitude of a portion of the putting green are displayed to the user or provided as part of a putting aid):
obtaining a slope information and a friction coefficient corresponding to the optimal batting path in the digital elevation model ([0011] predicting a motion of a simulated golf ball moving between the points along the trajectory based on the respective gradients between the adjacent points, a coefficient of rolling friction of the ball, and an initial condition of the ball, [0046] The deformation of the turf and the resulting coefficient of rolling friction, ρ, increase with the softness of the turf and the speed of the rolling golf ball); and
calculating the putting strength required for the golf ball to roll along the optimal batting path in the digital elevation model according to the slope information and friction coefficient ([0049], Equations (6a) and (6b), [0051] The path of the golf ball is determined by initial conditions, including launch direction and velocity, along with the equations of acceleration (2a) and (2b)).
Regarding Claim 6, Barkley discloses wherein the spatial multi-dimensional scanning device further comprises a display module (Col. 2 Lines 20-25 a flat panel color display 65/71, Col. 5 Lines 1-5 a display mounted in said housing for presentation of said graphical putting aid);
the method further comprises:
adding the display indicator to the spatial multi-dimensional information map (Col. 3 Lines 25-30 Once topographical data has been computed, the processor 67 constructs a color frame (display indicator) comprising any user-specified graphical putting aid); and
displaying the added spatial multi-dimensional information map on the display module (Col. 3 Lines 60-65 the processor 67 transmits this color frame, or graphical putting aid data 76, to the display 65/71, thus fulfilling the request 78 of the user for graphical putting aid).
However, Barkley is not relied upon disclosing the method further comprises: obtaining a display indicator corresponding to the putting strength; adding the optimal batting path to the spatial multi-dimensional information map.
Sweeney teaches wherein the method further comprises:
obtaining a display indicator corresponding to the putting strength (Fig. 10, [0066] These directional arrows can be made more or less dense depending on user preferences. The arrows can also be drawn to indicate magnitude of the slope by using different colors and/or shaft lengths. The arrows 40 in FIG. 10 use longer, red arrows to show more Severe slopes and shorter blue and purple arrows to show slopes of lesser magnitude); and
adding the optimal batting path to the spatial multi-dimensional information map ([0065] Another application of the invention is to use the computed aim data and path coordinate data as a basis for an overlay on video streams which shows the optimal path trajectory, or, once the ball has been stuck, which shows the actual path trajectory based on the known start and end coordinates of the ball (FIG. 9))).
Regarding Claim 7, Barkley discloses wherein the generating the optimal batting path from the starting point to the end point in the digital elevation model according to a preset path planning algorithm comprises:
generating an initial path in the digital elevation model (Col. 3 Lines 50-55 Suppose this point is short and right of the hole 84. The next estimated putt would then be adjusted longer and left proportionally).
However, Barkley is not relied upon disclosing generating an initial path from the starting point to the end point in the digital elevation model; extracting a slope information of the green in the digital elevation model; and adjusting the initial path through the slope information according to the path planning algorithm, to generate the optimal batting path.
Sweeney teaches generating an initial path from the starting point to the end point in the digital elevation model ([0055] We simply choose the optimal values from the grid points closest to the actual ball coordinate, or average the optimal values from surrounding points, and use those values as beginning values to solve for the actual (15.67,45.50) ball coordinate);
extracting a slope information of the green in the digital elevation model ([0040] The first step in calculating ball trajectories is determining the gradient of the green at Selected intervals); and
adjusting the initial path through the slope information according to the path planning algorithm, to generate the optimal batting path ([0051] The equations are run iteratively on a very small fixed time interval until the ball reaches its desired ending velocity, and deter mine the ball's position on the X-axis (x) and y-axis (y), [0055] Beginning the genetic Search with an initial data population which is close to optimal results in a very fast search for optimal conditions).
Regarding Claim 8, Barkley is not relied upon disclosing wherein the generating the optimal batting path from the starting point to the end point in the digital elevation model according to a preset path planning algorithm comprises: generating multiple candidate paths from the starting point to the end point in the digital elevation model according to a preset path planning algorithm; obtaining a terrain information corresponding to each candidate path in the digital elevation model; calculating a path validity corresponding to each candidate path according to the terrain information; and determining the optimal batting path from the candidate paths according to the multiple path validities.
Sweeney teaches wherein the generating the optimal batting path from the starting point to the end point in the digital elevation model according to a preset path planning algorithm comprises:
generating multiple candidate paths from the starting point to the end point in the digital elevation model according to a preset path planning algorithm ([0054] For example, FIG. 2 shows the different possible trajectories (candidate paths) of a putt given different putting styles or velocities (capture velocities) at which the ball reaches and/or passes through the target location, i.e., the hole 1. The three lines A, B, C show putts with velocities that 1.) stop at the hole 1-Line A, 2.) stop 6 inches past the hole 1-Line B, and 3.) stop 18 inches past the hole 1-Line C);
obtaining a terrain information corresponding to each candidate path in the digital elevation model ([0011] The trajectories are determined by computing gradients (terrain information) between adjacent points of the three dimensional surface model along each trajectory);
calculating a path validity corresponding to each candidate path according to the terrain information ([0054] a successful putt could follow any of these three trajectories, so it is necessary to be able to compute any or all of them so the individual golfer can choose a trajectory and launch conditions which match his putting preference, [0067] aim point data may be related to a green difficulty scoring system that ranks the relative difficulty of putting from different areas on the green to a pin position on the green… One measure of putting difficulty may be a ratio of the amount of break D to distance C to the hole, with a higher value Selected to represent a greater break-to-distance ratio. This ratio may be defined as: D/C (13)); and
determining the optimal batting path from the candidate paths according to the multiple path validities ([0018] deter mining for a plurality of location coordinates on a putting green optimal trajectories corresponding to a desired capture velocity for a golf ball to move from said location coordinate to an end point, and calculating putting parameters to propel a golf ball along a path substantially following the optimal trajectory).
Regarding Claim 18, Barkley is not relied upon disclosing wherein the batting path information at least comprises an optimal batting path, the generating a batting path information according to the elevation information and positions of the golf ball and hole comprises: constructing a digital elevation model of the green according to the elevation information; setting the position of the golf ball as a starting point and the position of the hole as an end point in the digital elevation model; and generating the optimal batting path from the starting point to the end point in the digital elevation model according to a preset path planning algorithm.
Sweeney teaches wherein the batting path information at least comprises an optimal batting path ([0018] Calculating the putting information includes deter mining for a plurality of location coordinates on a putting green optimal trajectories corresponding to a desired capture velocity for a golf ball to move from said location coordinate to an end point), the generating a batting path information according to the elevation information and positions of the golf ball and hole comprises:
constructing a digital elevation model of the green according to the elevation information ([0038] The Survey readings of the perimeter and elevation are then converted into a digital terrain model (DTM) data file which can be read by commercially available geographic information system (GIS) software);
setting the position of the golf ball as a starting point and the position of the hole as an end point in the digital elevation model ([0042] Once the gradient components of the surface has been generated, a computer program may simulate the rolling of a golf ball on that surface using known equations of motion, thus allowing a variety of putt paths to be predicted); and
generating the optimal batting path from the starting point to the end point in the digital elevation model according to a preset path planning algorithm ([0053] The process of calculating a successful putt trajectory given known values for green speed, capture speed, or starting and ending ball positions can be determined by using a number of non-linear Solving techniques).
Regarding Claim 19, Barkley is not relied upon disclosing wherein the batting path information further comprises a putting strength; after the generating the optimal batting path from the starting point to the end point in the digital elevation model according to a preset path planning algorithm, the method further comprises: obtaining a slope information and a friction coefficient corresponding to the optimal batting path in the digital elevation model; and calculating the putting strength required for the golf ball to roll along the optimal batting path in the digital elevation model according to the slope information and friction coefficient.
Sweeney teaches wherein the batting path information further comprises a putting strength ([0072] calculating a putting parameter for propelling the golf ball from the start position to the target location based on a trajectory corresponding to a desired capture velocity of the ball, wherein the trajectory has a start point substantially corresponding to the start position and an end point substantially corresponding to the target location. The putting parameters displayed may include an aim angle, an initial velocity);
after the generating the optimal batting path from the starting point to the end point in the digital elevation model according to a preset path planning algorithm, the method further comprises ([0011] The trajectories are determined by computing gradients between adjacent points of the three dimensional surface model along each trajectory… Indicia indicative of a slope direction and slope magnitude of a portion of the putting green are displayed to the user or provided as part of a putting aid):
obtaining a slope information and a friction coefficient corresponding to the optimal batting path in the digital elevation model ([0011] predicting a motion of a simulated golf ball moving between the points along the trajectory based on the respective gradients between the adjacent points, a coefficient of rolling friction of the ball, and an initial condition of the ball, [0046] The deformation of the turf and the resulting coefficient of rolling friction, ρ, increase with the softness of the turf and the speed of the rolling golf ball); and
calculating the putting strength required for the golf ball to roll along the optimal batting path in the digital elevation model according to the slope information and friction coefficient ([0049], Equations (6a) and (6b), [0051] The path of the golf ball is determined by initial conditions, including launch direction and velocity (putting strength), along with the equations of acceleration (2a) and (2b)).
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Barkley et al. (US 8,449,409 B1), in view of Hendrix et al. (US 2020/0398138 A1).
Regarding Claim 9, Barkley discloses wherein after the complete a path planning for the green according to the batting path information, the method further comprises:
updating the batting path information according to the elevation information, the position of the hole and the changed position of the golf ball (Col. 3 Lines 50-55 With these locations, a rough estimate of a successful putt is computed, and the calculated point at which the golf ball 80 stops (changed position of the golf ball) is temporarily saved… The next estimated putt (updated batting path information) would then be adjusted longer and left proportionally).
However, Barkley is not relied upon disclosing if detecting that the position of the golf ball has changed and a distance to the position of the hole is greater than a preset distance, obtaining a changed position of the golf ball.
Hendrix teaches if detecting that the position of the golf ball has changed and a distance to the position of the hole is greater than a preset distance, obtaining a changed position of the golf ball ([0084] The ball flight (changed position of the golf ball) data may be calculated based on the approximate start position and the approximate rest position of the golf ball 104 and may include, for example, a driving distance or other distance of the golf ball 104; an angle between the approximate start position and approximate rest position of the golf ball 104; a distance between the approximate rest position of the golf ball 104 and a fairway; a distance between the approximate rest position of the golf ball 104 and a green; a distance between the approximate rest position of the golf ball 104 and a portion of a green; a distance between the approximate rest position of the golf ball 104 and a flagstick (position of the golf ball and a distance to the hole is greater than a preset distance); or a distance between the approximate rest position of the golf ball 104 and a hazard).
Barkley and Hendrix are both considered to be analogous to the claimed invention, because they are in the same field of golf analysis tools that take various measurements. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filling date of the applicant’s invention for modifying the a path planning method for putting on the green, applied to a spatial multi-dimensional scanning device, as disclosed by Barkley, further including if detecting that the position of the golf ball has changed and a distance to the position of the hole is greater than a preset distance, obtaining a changed position of the golf ball, as taught by Hendrix for the purpose of associating location information of a golf ball with data for sensed swing characteristics (Hendrix, [0084]).
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Barkley et al. (US 8,449,409 B1), in view of Sweeney (US 2005/0101415 A1), and in further view of Yasuyuki et al. (WO 2014027477 A1).
Regarding Claim 13, Barkley is not relied upon disclosing wherein the path planning algorithm comprises an A* algorithm, a Dijkstra's algorithm or a shortest path algorithm.
Yasuyuki teaches wherein the path planning algorithm comprises an A* algorithm, a Dijkstra's algorithm or a shortest path algorithm ([0033] Based on the two pieces of position information representing the positions of the two points, the map information server 4 calculates the route between the two points and the required time required to move the route by, for example, the Dijkstra's Algorithm ), An A-star method or the like, and a route required time computing section 41 (an example of a computing section) that can be computed using a known computing method).
Barkley and Yasuyuki are both considered to be analogous to the claimed invention, because they are in the same field of golf aids. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filling date of the applicant’s invention for modifying the a path planning method for putting on the green, applied to a spatial multi-dimensional scanning device, as disclosed by Barkley, as previously modified by Sweeney, further including wherein the path planning algorithm comprises an A* algorithm, a Dijkstra's algorithm or a shortest path algorithm, as taught by Yasuyuki for the purpose of determining the shortest route that would take the shortest amount of time (Yasuyuki, [0033]).
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Barkley et al. (US 8,449,409 B1), in view of Sweeney (US 2005/0101415 A1), and in further view of Hall et al. (US 2022/0387873 A1).
Regarding Claim 14, Barkley discloses wherein the performing a target detection on the spatial multi-dimensional information map to determine positions of a golf ball and a hole in the spatial multi-dimensional information map comprises:
wherein the object detection mode comprises position information of a golf ball and a hole (Col. 3 Lines 40-45 First, the golf ball's 80 and hole's 84 locations are determined with a simple image processing algorithm); and
determine positions of the golf ball and hole (Col. 3 Lines 40-45 First, the golf ball's 80 and hole's 84 locations are determined with a simple image processing algorithm).
However, Barkley is not relied upon disclosing wherein the performing a target detection on the spatial multi-dimensional information map to determine positions of a golf ball and a hole in the spatial multi-dimensional information map comprises: collecting and annotating golf green image datasets; using an object detection algorithm for model training; inputting the spatial multi-dimensional information map into the trained object detection model, wherein the object detection mode is configured to output bounding boxes that comprise position information of a golf ball and a hole; and classifying the bounding boxes to determine positions of the golf ball and hole.
Hall teaches wherein the performing a target detection on the spatial multi-dimensional information map to determine positions of a golf ball and a hole in the spatial multi-dimensional information map comprises:
collecting and annotating golf green image datasets ([0065] Once the images are filtered, the next step is to annotate the images. Annotation here refers to generating the coordinates of the bounding boxes that envelop the golf balls in the collected images. It is this information which the ML models are trained to detect and track the golf balls);
using an object detection algorithm for model training ([0094] The inference outputs of an object detection algorithm are the bounding box coordinates and the class number (class id) of the detected objects);
inputting the spatial multi-dimensional information map into the trained object detection model, wherein the object detection mode is configured to output bounding boxes that comprise position information of a golf ball and a hole ([0094] In a preferred embodiment, we employ an object detection algorithm to detect the balls from the video. Additionally, an object tracking algorithm will be employed to identify the unique balls as they transit across the frames. The object detection algorithm in general predicts the position and type of the objects of interest in an image. In our scenario, the objects of interest are the golf balls); and
classifying the bounding boxes to determine positions of the golf ball and hole2 ([0094] The inference outputs of an object detection algorithm are the bounding box coordinates and the class number (class id) of the detected objects. A bounding box is the rectangular box with the minimum area that envelopes an object of interest. The class id is a unique identifier that denotes the class of an object. The players may be assigned with the balls of a specific color that is unique to them, so that the object detection model can directly map each ball to its corresponding player, [0098] Also from the color classifier output, we have mapped each of the balls in the playfield to its corresponding player. By processing these two bits of information, we can map each shot to its corresponding player in the chronological order within the game. This information is further used for the scoring of each shot).
Barkley and Hall are both considered to be analogous to the claimed invention, because they are in the same field of golf analysis systems and/or tools. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filling date of the applicant’s invention for modifying the a path planning method for putting on the green, applied to a spatial multi-dimensional scanning device, as disclosed by Barkley, as previously modified by Sweeney, further including wherein the performing a target detection on the spatial multi-dimensional information map to determine positions of a golf ball and a hole in the spatial multi-dimensional information map comprises: collecting and annotating golf green image datasets; using an object detection algorithm for model training; inputting the spatial multi-dimensional information map into the trained object detection model, wherein the object detection mode is configured to output bounding boxes that comprise position information of a golf ball and a hole; and classifying the bounding boxes to determine positions of the golf ball and hole, as taught by Hall for the purpose of tracking golf balls, and estimating the ball’s deceleration, velocity, direction, and current position, even for multiple players at once (Hall, [0094]-[0100]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
McDonald et al. (US 2003/0017890 A1) teaches an apparatus and method for improving the playing of golf (Abstract).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HAMID TARIQ HAFIZ whose telephone number is (571) 272-4629. The examiner can normally be reached 7:30 AM - 5:00 PM, Monday through Thursday.
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/HAMID TARIQ HAFIZ/
Examiner, Art Unit 3715
/ROBERT J UTAMA/Primary Examiner, Art Unit 3715
1 Claims 2, 3, 16, and 17 are not rejected under 35 USC § 101, because they include additional elements that go beyond the abstract idea (e.g. structured light acquisition modules, visible light acquisition modules, and ranging modules). Therefore claims 2, 3, 16, and 17 amount to significantly more than the judicial exception, and qualify as eligible subject matter under 35 USC § 101.
2 Barkley discloses identifying the positions of a golf ball and a hole, while Hall teaches bounding boxes that determine the position of golf balls. It would have been obvious to one of ordinary skill in the art, before the effective filing date of the invention to modify the identification of the positions of a golf ball and a hole, as taught by Barkley, with the bounding box object tracking, as taught by Hall, because the objective of golf is to hit the golf ball into the whole in as few hits (swings, strokes, etc…) as possible. Although Hall does not explicitly disclose bounding boxes for golf holes, determining the position of a golf hole is inherent to playing golf. In addition, Barkley discloses determining the position of a golf ball and a golf hole. Therefore, the combination renders the following claim limitations obvious: “inputting the spatial multi-dimensional information map into the trained object detection model, wherein the object detection mode is configured to output bounding boxes that comprise position information of a golf ball and a hole”; and “classifying the bounding boxes to determine positions of the golf ball and hole”.
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