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
Acknowledgment is made of applicant’s claim for priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application SE2250688-5, filed on 06/08/2022.
Status of Claims
Claims 1-8, 14, 17, and 19-20 are amended.
Claims 9, 18 and 19 are cancelled or previously cancelled.
Claims 1-8, 10-17, and 20 are pending.
Response to Arguments/Remarks
35 U.S.C. 101
Applicant’s arguments have been fully considered and are persuasive. The 35 USC § 101 has been withdrawn due to cancellation of Claim 19.
35 U.S.C. 112
Applicant did not set forth any arguments on the 35 U.S.C. 112. No attempt to correct was made. The 35 U.S.C. 112 stands.
Applicant’s arguments with respect to claims 1-8, 10-17, and 19-20 have been considered but are moot in view of the new ground(s) of rejection as necessitated by applicant's amendments. After the cancellation, claims 1-8, 10-17, and 20 are pending.
Claim Interpretation
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. Under a broadest reasonable interpretation (BRI), words of the claim must be given their plain meaning, unless such meaning is inconsistent with the specification. The plain meaning of a term means the ordinary and customary meaning given to the term by those of ordinary skill in the art at the relevant time. The ordinary and customary meaning of a term may be evidenced by a variety of sources, including the words of the claims themselves, the specification, drawings, and prior art. However, the best source for determining the meaning of a claim term is the specification - the greatest clarity is obtained when the specification serves as a glossary for the claim terms. The words of the claim must be given their plain meaning unless the plain meaning is inconsistent with the specification. 2111.01 (I). See also In re Marosi, 710 F.2d 799, 802, 218 USPQ 289, 292 (Fed. Cir. 1983) ("'[C]laims are not to be read in a vacuum, and limitations therein are to be interpreted in light of the specification in giving them their ‘broadest reasonable interpretation.'"2111.01 (II).
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “control unit” in claims 1 and 10. The “control unit” is only doing calculations which is software. Suggested update would be “a control having a neural network….”.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-8, 10-17, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Park et al. [US20200074239, now Park], in view of Suresh et al. [US20200050893, now Suresh], further in view of Minear et al. [US20100207936, now Minear], with Tsishkou et al. [US20190086546, now Tsish].
Claim 1
Park discloses a marine surround sensing system for controlling a marine vessel[see at least Park, ¶ 0052 (“According to another aspect of the present invention, an autonomous navigation method of a ship”)] comprises:
Light Detection And Ranging, LiDAR, sensors mounted around the marine vessel for registering surroundings of the marine vessel[see at least Park, ¶ 0194 – 0195 (discusses “object information” obtained through sensors (such as a radar or a LiDAR ) and creates on object Map… “The obstacle map refers to a means for presenting object information.”)],
a control unit with a neural network to process information about the registered surroundings which has been registered by the LiDAR sensors, wherein the information registered by the LiDAR sensors is in the form of a 3D point cloud, wherein the processing [see at least Park, ¶ 0042 (discusses neural network and how it is used to gather data); 0104 and 0195 (discuss the formation of 3D maps.)] comprises;
a first projection, by the control unit, of the 3D point cloud into one or two 2D maps; segmentation, by the neural network in the control unit, of the one or two 2D maps, wherein an output of the segmentation is a segmented 2D map with class information for each point in the one or two 2D maps and a second projection, by the control unit of the segmented 2D map back to the 3D point cloud [see at least Park, ¶ 0048 (more on the neural network and obtaining data from images); 0140; 0195; 0003 (“The present invention relates to a situation awareness method and device using image segmentation”); 0203 (discusses unsailable regions)]; and,
where the control unit is programmed to visualize the registered surroundings based on LiDAR data enriched by the neural network displaying an image or map representing the 3D point cloud from the second projection, and wherein the enrichment comprises classification of the registered information into class objects in order to distinct between different types of objects in the surroundings, wherein the control unit is arranged to make decisions adapted to the visualized objects nearby the marine vessel depending on their class objects [see at least Park, ¶ 0103 (“A neural network which performs image segmentation to sense surroundings may receive an image and output object information.”); 0196 (“The obstacle map may include a plurality of unit regions.”); 0208 (discusses updated regions can “be determined according to an obstacle detection sensor, such as a camera, a radar, or a LiDAR. For example, an update region may be determined by the angle of view and/or the maximum observation distance of a camera.”)].
Park does not disclose some of the aspects of a marine vessel that Suresh does teach [see at least Suresh ¶ 0017 (discusses objects); mounted LiDAR sensors [see at least Suresh ¶ 0066 (“LiDAR’s”)]; surroundings analysis [see at least Suresh, ¶ 0014 (discusses “identify and classify objects in images from a sensor system disposed on a maritime vessel…”)]; positional information using trained neural network [see at least Suresh, ¶ 0073 (further discusses images and neural networks and use of the cloud and “The neural network can provide a bounding box (e.g., x cross y) or other graphical shape (two-dimensional or three-dimensional) around an object in an image, which can size the object in the image using various methods”)].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the situation awareness techniques of Park, with the object detection network with images to identify and classify objects in the images of Suresh. Providing a more effective, efficient and safer technique to help a vessel avoid obstacles and other hazards at sea and in ports.
Neither Park or Suresh specifically disclose/teach but Minear more specifically teaches the techniques for taking 2D and 3D images and combine the information needed for the image to have distinct and show the obstacles [see at least Minear, Abstract (“Method and system for combining a 2D image with a 3D point cloud for improved visualization of a common scene as well as interpretation of the success of the registration process. The resulting fused data contains the combined information from the original 3D point cloud and the information from the 2D image. The original 3D point cloud data is color coded in accordance with a color map tagging process. By fusing data from different sensors, the resulting scene has several useful attributes relating to battle space awareness, target identification, change detection within a rendered scene, and determination of registration success.”); 0002 (discusses “two-dimensional and three dimensional image data, and more particularly methods for visual interpretation of registration performance of 2D and 3D image data.”); 0008 (“The invention concerns a method and system for combining a 2D image with a 3D point cloud for improved visualization of a common scene as well as interpretation of the success of the registration process.” Thus indicates that the 3D and 2D data is combined to form maps)].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the situation awareness techniques of Park, with the object detection network with images to identify and classify objects in the images of Suresh, further with the ability to a 3D point cloud data and 2D data to provide maps of Minear. Providing a more effective, efficient and safer technique to help a vessel avoid obstacles and other hazards at sea and in ports.
Neither Park, Suresh, or Minear specifically disclose/teach the exact wording for the amended limitations, Minear does teach the concept in general but Tsish more closely teaches and clarifies the rejection for the amended limitations; wherein the one or two 2D maps comprise a depth map and/or an intensity map derived from the 3D point cloud; segmentation, by the neural network in the control unit, of the one or two 2D maps based on the depth map and/or the intensity map [see at least Tsish, Abstract (shows an overview of data from a 3D point cloud to produce a 2D rendering including intensity and depth data); ¶ 0005 (“ only intensity data is presented in form of 2D image maps,”); 0007 (discusses intensity measurements and other methods for creation of data rich output); 0018 (“depth sensor”)].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the situation awareness techniques of Park, with the object detection network with images to identify and classify objects in the images of Suresh, with the ability to a 3D point cloud data and 2D data to provide maps of Minear, further with the using of 3D map data to produce a 2D map. Providing a more effective, efficient and safer technique to help a vessel avoid obstacles and other hazards at sea and in ports.
Claim 2
Park, Suresh, Minear and Tsish disclose/teach the system of Claim 1.
Park further discloses a helm station to visualize the registered surroundings and to provide input for manually controlling a driveline of the marine vessel [see at least Park, ¶ 0054; 0243 (discusses control signal ); 0248 (discusses control by a person)].
Park does disclose this limitation but Suresh also teaches this limitation with more clarity [see at least Suresh ¶ 0082 (“Additionally, instructions may include suggestions to a pilot, helmsman, or captain to make any of these adjustments.”)].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the situation awareness techniques of Park, with the object detection network with images to identify and classify objects in the images of Suresh. Providing a more effective, efficient and safer technique to help a vessel avoid obstacles and other hazards at sea and in ports.
Claim 3
Park, Suresh, Minear and Tsish disclose/teach the system of Claim 1.
Park further discloses classified information from the classification is disclosed as a three dimensional, 3D, point cloud visualization with positional information and class information [see at least Park, ¶ 0195; 0196 (“The obstacle map may include a plurality of unit regions. The plurality of unit regions may be presented in various ways according to classification criteria. As an example, the obstacle map may include a sailable region, an unsailable region, and an unknown region which may not be determined to be sailable or not.”)].
Park does disclose this limitation but Suresh also teaches this limitation with more clarity [see at least Suresh, ¶ 0111 (“FIG. 6 is a flowchart of an example situational awareness system 600 in accordance with an embodiment.”)].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the situation awareness techniques of Park, with the object detection network with images to identify and classify objects in the images of Suresh. Providing a more effective, efficient and safer technique to help a vessel avoid obstacles and other hazards at sea and in ports.
Claim 4
Park, Suresh, Minear and Tsish disclose/teach the system of Claim 1.
Park further discloses classified information from the classification is disclosed as a probability map [see at least Park, ¶ 0203-0204 (discusses use of probability in determining presence of objects and obstacle maps)].
Park does disclose this limitation but Suresh also teaches this limitation with more clarity [see at least Suresh,, ¶ 0073 (Discusses classification of objects); 0158; 0173 (both deal with Probabilistic calculations].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the situation awareness techniques of Park, with the object detection network with images to identify and classify objects in the images of Suresh. Providing a more effective, efficient and safer technique to help a vessel avoid obstacles and other hazards at sea and in ports.
Claim 5
Park, Suresh, Minear and Tsish disclose/teach the system of Claim 4.
Park further discloses the probability map is a two dimensional, 2D, point cloud visualization with positional information and class information [see at least Park, ¶ 0195].
Park does disclose this limitation but Suresh also teaches this limitation with more clarity [see at least Suresh, ¶ 0103 (discusses map overlays and visualization)].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the situation awareness techniques of Park, with the object detection network with images to identify and classify objects in the images of Suresh. Providing a more effective, efficient and safer technique to help a vessel avoid obstacles and other hazards at sea and in ports.
Tsish more specifically teaches probability map is a two dimensional, 2D, point cloud visualization with positional information and class information [see at least Tsish, Abstract (shows an overview of data from a 3D point cloud to produce a 2D rendering including intensity and depth data); ¶ 0005 (“ only intensity data is presented in form of 2D image maps,”); 0007 (discusses intensity measurements and other methods for creation of data rich output); 0018 (“depth sensor”)].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the situation awareness techniques of Park, with the object detection network with images to identify and classify objects in the images of Suresh, with the ability to a 3D point cloud data and 2D data to provide maps of Minear, further with the using of 3D map data to produce a 2D map. Providing a more effective, efficient and safer technique to help a vessel avoid obstacles and other hazards at sea and in ports.
Claim 6
Park, Suresh, Minear and Tsish disclose/teach the system of Claim 4.
Park further discloses the probability map is a three dimensional, 3D, point cloud visualization with positional information and class information [see at least Park, ¶ 0195].
Claim 7
Park, Suresh, Minear and Tsish disclose/teach the system of Claim 1.
Park further discloses the classification is done with a projection-based method for semantic classification of a three dimensional, 3D, point cloud [see at least Park, ¶ 0137 (“Obtaining labelling data including distance information will be described in further detail. Distance information may be obtained using a depth camera. The depth camera may be a stereo type, a structured pattern type, a TOF type, or the like or may be a combination of two or more thereof. It is possible to generate one piece of labelling data by obtaining distance information of each pixel in an image from the depth camera. In addition to this, various methods for obtaining distance information may be used.”)].
Claim 8
Park, Suresh, Minear and Tsish disclose/teach the system of Claim 1.
Park further discloses each point in the visualizations is coloured with a colour of a class object [see at least Park, ¶ 0252 (“Also, it is possible to output obstacle characteristics including the distance, speed, danger, size, and collision probability of an obstacle. Obstacle characteristics may be output using color, which may vary according to the distance, speed, danger, size, and collision probability of an obstacle.”); 0255 (describes use of color regions)].
9. (Canceled)
Claim 10
Park, Suresh, Minear and Tsish disclose/teach the system of Claim 1.
Park further discloses the control unit is arranged to make decisions in such a way that: a. if there is another marine vessel within a predetermined distance, the control unit automatically lowers the speed of the marine vessel below a predetermined speed to avoid getting too close to the other marine vessel while, b. If instead a dock is registered, the marine vessel is allowed to drive faster than the predetermined speed when approaching the dock, since a dock is not a movable object compared to the other marine vessel [see at least Park, ¶ 0210 (discusses control); 0214 (Discusses image evaluation to obtain the best data for any situation); 0223; 0235 (discusses FIG. 29 obstacle updates); 0242 (talks about control)].
Park does disclose this limitation but Suresh also teaches control of a vessel with more clarity [see at least Suresh, Claim 1 (“1. A method comprising: training, using a processor, an object detection network with training images to identify and classify objects in images from a sensor system disposed on a maritime vessel; identifying objects in the images using the processor in an offline mode; classifying the objects in the images using the processor in the offline mode generating heat maps in the offline mode; and sending instructions regarding operation of the maritime vessel, using the processor, based on the objects that are identified, wherein the instructions include a speed or a heading.”)].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the situation awareness techniques of Park, with the object detection network with images to identify and classify objects in the images of Suresh. Providing a more effective, efficient and safer technique to help a vessel avoid obstacles and other hazards at sea and in ports.
Claim 11
Park, Suresh, Minear and Tsish disclose/teach the system of Claim 1
Park further discloses a marine vessel comprising the marine surround sensing system [see at least Park, ¶ 0052 (“marine image”); 0524 (“ a ship-oriented obstacle map, an existing path, and an obstacle-avoiding path may be output in a bird's eye view.”)].
Park does disclose this limitation but Suresh also teaches a marine vessel [see at least Suresh, Abstract (“maritime vessel”)].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the situation awareness techniques of Park, with the object detection network with images to identify and classify objects in the images of Suresh. Providing a more effective, efficient and safer technique to help a vessel avoid obstacles and other hazards at sea and in ports.
Claim 12
Claim 12 has similar limitations to claim 1, therefore claim 12 is rejected with the same rationale as claim 1.
Claim 13
Claim 13 has similar limitations to claim 3, therefore claim 13 is rejected with the same rationale as claim 3.
Claim 14
Claim 14 has similar limitations to claim 4, therefore claim 14 is rejected with the same rationale as claim 4.
Claim 15
Claim 15 has similar limitations to claim 5, therefore claim 15 is rejected with the same rationale as claim 5.
Claim 16
Claim 16 has similar limitations to claim 6, therefore claim 16 is rejected with the same rationale as claim 6.
Claim 17
Claim 17 has similar limitations to claim 7, therefore claim 17 is rejected with the same rationale as claim 7.
Claim 18. (Canceled)
Claim 19 (Cancelled)
Claim 20
Claim 20 has similar limitations to claim 1, therefore claim 20 is rejected with the same rationale as claim 1.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
G. Pang and U. Neumann, "Fast and Robust Multi-view 3D Object Recognition in Point Clouds," 2015 International Conference on 3D Vision, Lyon, France, 2015, pp. 171-179.
Abstract:
Recognition of three dimensional (3D) objects in point clouds is a challenging problem. Existing methods often require prior segmentation or 3D descriptor training and matching, both time consuming and complex processes, especially for large-scale industrial or urban street data. We describe a new recognition approach that projects a 3D point cloud into several 2D depth images from multiple viewpoints, transforming the 3D recognition problem into a series of 2D detection problems. This method reduces complexity, stabilizes performance, and significantly speeds up the recognition process, without any requirement for object segmentation or detector training. Experiments validate the superiority of our method over several state-of-the-art methods on examples from industrial and street data scans.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOAN T GOODBODY whose telephone number is (571) 270-7952. The examiner can normally be reached on M-TH 7-3 (US Eastern time).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, RACHID BENDIDI can be reached at (571) 272-4896. The Fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300.
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/JOAN T GOODBODY/
Primary Examiner, Art Unit 3664
(571) 270-7952
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