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`UNITED STATES PATENT AND TRADEMARK OFFICE
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`———————
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`BEFORE THE PATENT TRIAL AND APPEAL BOARD
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`———————
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`TESLA, INC.,
`Petitioner
`
`v.
`
`INTELLECTUAL VENTURES II LLC,
`Patent Owner.
`
`———————
`
`IPR2025-00342
`U.S. Patent No. 7,336,805
`
`
`PETITION FOR INTER PARTES REVIEW
`UNDER 35 U.S.C. § 312 AND 37 C.F.R. § 42.104
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`
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`

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`
`
`IPR2025-00342 Petition
`Inter Partes Review of 7,336,805
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`TABLE OF CONTENTS
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`Petitioner’s Exhibit List ............................................................................................. 4
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`I.
`
`II.
`
`Introduction ...................................................................................................... 5
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`Grounds for standing ....................................................................................... 5
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`III. Note .................................................................................................................. 5
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`IV. The ’805 patent ................................................................................................ 6
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`V.
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`Level of ordinary skill in the art ...................................................................... 7
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`VI. Claim construction ........................................................................................... 7
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`VII. Relief requested ............................................................................................... 7
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`VIII. Identification of how the claims are unpatentable ........................................... 8
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`A.
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`B.
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`C.
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`Challenged claims ................................................................................ 8
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`Statutory grounds for challenges .......................................................... 8
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`Ground 1: Claims 1-2 and 9-10 are obvious over Broggi-
`Huttenlocher-Brady. ............................................................................. 9
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`D. Ground 2: Claims 6-8 and 11 are obvious over Broggi-
`Huttenlocher-Brady-Bertozzi. ............................................................ 61
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`IX. Broggi, Huttenlocher, and Bertozzi are Printed Publications .......................81
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`X. Discretionary denial is inappropriate .............................................................82
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`A. No basis for §325(d) denial ................................................................ 82
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`B.
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`C.
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`No basis for Fintiv denial ................................................................... 82
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`No basis for General Plastic denial ................................................... 85
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`XI. Conclusion .....................................................................................................85
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`2
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`XII. Mandatory notices .........................................................................................86
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`IPR2025-00342 Petition
`Inter Partes Review of 7,336,805
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`A.
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`B.
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`C.
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`Real party-in-interest .......................................................................... 86
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`Related matters ................................................................................... 86
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`Lead and back-up counsel and service information ........................... 86
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`Certificate of Word Count .......................................................................................88
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`Certificate of Service ...............................................................................................89
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`IPR2025-00342 Petition
`Inter Partes Review of 7,336,805
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`PETITIONER’S EXHIBIT LIST
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`U.S. Pat. No. 7,336,805 to Gehring et al. (“the ’805 patent”)
`
`Prosecution History of U.S. Pat. No. 7,336,805 (U.S. Application
`No. 11/154,772) (“the ’772 application”)
`
`Declaration of Dr. Jeffrey Rodriguez under 37 C.F.R. § 1.68
`Curriculum Vitae of Dr. Jeffrey Rodriguez
`
`“Visual Perception of Obstacles and Vehicles for Platooning,”
`Broggi et al. (“Broggi”)
`
`“Object Recognition Using Alignment,” Daniel Huttenlocher
`(“Huttenlocher”)
`
`U.S. Patent No. 5,434,927 to Brady et al. (“Brady”)
`“Automatic Vehicle Guidance: The Experience of the ARGO
`Autonomous Vehicle,” Broggi, Bertozzi, et al. (“Bertozzi”)
`
`Microsoft Computer Dictionary, 3rd ed., 1997, excerpts
`
`IV’s Complaint, Intellectual Ventures II, LLC v. Tesla, Inc., No.
`6:24-cv-188-ADA (WDTX)
`
`Proposed Scheduling Order, Intellectual Ventures II, LLC v. Tesla,
`Inc., No. 6:24-cv-188-ADA (WDTX)
`Statistics on District Court Timing
`
`Interim Procedure for Discretionary Denials in AIA Parallel
`District Court Litigation, June 21, 2022
`
`IV’s Preliminary Infringement Contentions, Intellectual Ventures
`II, LLC v. Tesla, Inc., No. 6:24-cv-188-ADA (WDTX)
`
`Declaration of Sylvia Hall-Ellis, Ph.D.
`
`
`
`
`
`
`Ex.1001
`
`Ex.1002
`
`Ex.1003
`Ex.1004
`
`Ex.1005
`
`Ex.1006
`
`Ex.1007
`Ex.1008
`
`Ex.1009
`
`Ex.1010
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`Ex.1011
`
`Ex.1012
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`Ex.1013
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`Ex.1014
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`Ex.1015
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`4
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`I.
`
`INTRODUCTION
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`IPR2025-00342 Petition
`Inter Partes Review of 7,336,805
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`U.S. Patent 7,336,805 (“the ’805 patent,” Ex.1001) is directed to “a method
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`for assisting vehicle guidance on the basis of image data[.]” Ex.1001, 1:6‑9.
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`However, as shown in this Petition, claims 1-2 and 6-11 (the “Challenged Claims”)
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`recite well-known aspects of vehicle guidance and image recognition. Pursuant to
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`35 U.S.C. §§311, 314(a), and 37 C.F.R. §42.100, Tesla, Inc. (“Petitioner”)
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`respectfully requests that the Board institute review and find the Challenged
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`Claims unpatentable.
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`II. GROUNDS FOR STANDING
`
`Petitioner certifies that the ’805 patent is eligible for IPR and that Petitioner
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`is not estopped from requesting IPR.
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`III. NOTE
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`Petitioner cites to exhibits’ original page numbers, unless noted otherwise.
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`Emphasis in quoted material has been added. Claim terms are presented in italics.
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`IV. THE ’805 PATENT
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`IPR2025-00342 Petition
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`The ’805 patent describes a method for docking assistance using image
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`analysis. Ex.1001, Abstract. A vehicle is equipped with a camera (image sensor 22
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`on vehicle 20 in Figure 2) to obtain image data. Ex.1001, 2:56-57.
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`Ex.1001, Fig. 2 (annotated)
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`
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`The obtained images are analyzed to locate objects, e.g., cargo door 26 in
`
`Figure 2. Ex.1001, Abstract, 7:13-29. The obtained image data is broken down into
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`edge segments, and interrelationships between the edge segments are stored in a
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`tree structure. Ex.1001, 3:37-39; 4:43-45. The edge segments are then analyzed to
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`check for the presence of a geometric object similar to a shape (e.g., geometric
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`form) associated with a potential destination of the vehicle (e.g., rectangle for the
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`6
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`cargo door of the dock). Ex.1001, 3:40-43. The detected geometric objects are then
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`IPR2025-00342 Petition
`Inter Partes Review of 7,336,805
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`“analyzed for plausibility” using a known matching algorithm. Ex.1001, 2:41-43;
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`3:3-8; 3:47‑50. Plausible objects then undergo an additional “acceptance analysis.”
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`Ex.1001, 3:41-54. Accepted object(s) are then used in calculating a trajectory to
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`assist in vehicle guidance to the dock. Ex.1001, 3:61-66.
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`V. LEVEL OF ORDINARY SKILL IN THE ART
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`A person of ordinary skill in the art in June 2004 (“POSITA”) would have
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`had a bachelor’s degree in electrical engineering, computer engineering, computer
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`science, or a related subject, and four years of work experience in image
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`processing, automated vehicle control/navigation, or a related field. Less
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`experience may be necessary with additional education (e.g., a master’s degree),
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`and likewise, less education may be necessary with additional work experience
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`(e.g., 5-7 years). Ex.1003, ¶14.
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`VI. CLAIM CONSTRUCTION
`
`For purposes of this proceeding and the grounds presented herein, no claim
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`term requires express construction. Nidec Motor Corp. v. Zhongshan Broad Ocean
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`Motor Co., 868 F.3d 1013, 1017 (Fed. Cir. 2017). Ex.1003, ¶34.
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`VII. RELIEF REQUESTED
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`Petitioner asks that the Board institute an IPR trial and find the Challenged
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`Claims unpatentable in view of the analysis below.
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`Inter Partes Review of 7,336,805
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`VIII. IDENTIFICATION OF HOW THE CLAIMS ARE UNPATENTABLE
`A. Challenged claims
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`Petitioner challenges claims 1-2 and 6-11.
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`B.
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`Statutory grounds for challenges
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`Grounds
`#1
`#2
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`Claims
`1-2, 9-10
`6-8, 11
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`Pre-AIA Basis (§103)
`Broggi, Huttenlocher, and Brady
`Broggi, Huttenlocher, Brady, and Bertozzi
`
`
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`Broggi (Ex.1005): “Visual Perception of Obstacles and Vehicles for
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`Platooning” (“Broggi”). Broggi was publicly available by at least September 1,
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`2000. See §IX (citing Ex.1015). Broggi is prior art under pre-AIA §§102(a)-(b).
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`Huttenlocher (Ex.1006): “Object Recognition Using Alignment”
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`(“Huttenlocher”). Huttenlocher was publicly available by at least September 26,
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`1989. See §IX (citing Ex.1015). Huttenlocher is prior art under pre-AIA §§102(a)-
`
`(b).
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`Brady (Ex.1007): U.S. Patent 5,434,927 (“Brady”) issued July 18, 1995.
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`Brady is prior art under pre-AIA §§102(a)-(b), (e).
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`Bertozzi1 (Ex.1008): “Automatic Vehicle Guidance: The Experience of the
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`
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`ARGO Autonomous Vehicle” (“Bertozzi”). Bertozzi was publicly available by at
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`least September 27, 1999. See §IX (citing Ex.1015). Bertozzi is prior art under pre-
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`AIA §§102(a)-(b).
`
`Petitioner’s §103 obviousness grounds rely on the combined teachings of the
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`references, not physical incorporation of elements. See In re Mouttet, 686 F.3d
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`1322, 1332 (Fed. Cir. 2012).
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`C. Ground 1: Claims 1-2 and 9-10 are obvious over Broggi-
`Huttenlocher-Brady.
`
`1.
`
`Broggi
`
` Broggi describes an “autonomous vehicle equipped with vision systems and
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`automatic steering capability” that performs lane following and platooning, “the
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`automatic following of a preceding vehicle.” Ex.1005, 164-165. Broggi provides
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`an example of its motor vehicle and corresponding equipment, including cameras,
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`speakers, and a monitor, in Figure 1:
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`1 While the lead author of Ex.1008 is the same as Ex.1005 (Alberto Broggi),
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`Petitioner refers to Ex.1008 by the second-named author (Massimo Bertozzi) to
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`distinguish from Ex.1005.
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`Ex.1005, Fig. 1.
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`
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`Broggi’s motor vehicle uses obtained images to localize and track objects
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`Ex.1005, 164. For example, during platooning, Broggi analyzes “a specific region
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`of the image” to detect a preceding vehicle. Ex.1005, 170. A “traditional pattern
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`matching technique” is used to detect a bounding box of the preceding vehicles by
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`(1) determining “two corners representing the bottom of the bounding box around
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`the vehicle,” and (2) detecting “the top part of the bounding box, which is looked
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`for in a specific region whose location is again determined by perspective and size
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`constraints.” Ex.1005, 170‑171.
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`Bounding Box
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`Preceding Vehicle
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`Ex.1005, Fig. 16 (annotated)
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`A desired path for the vehicle is then calculated based on the determined
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`location of the preceding vehicle, as reflected in Figure 21:
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`Preceding Vehicle Location
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`Motor Vehicle
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`Ex.1005, Fig. 21 (annotated)
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`11
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`2. Huttenlocher
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`IPR2025-00342 Petition
`Inter Partes Review of 7,336,805
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`Huttenlocher describes a pattern matching technique for identifying an
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`object—e.g., a preceding vehicle (reflected in Figure 11)—in an image that “uses
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`edge-based shape features for matching.” Ex.1006, 373.
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`Ex.1006, Fig. 11 (in part)
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`
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`After using an edge detector on an image, the edges are segmented and edge
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`segments are stored in a hierarchical tree structure. Ex.1006, 373. The hierarchical
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`segmentations “form a (multi-rooted) tree, where each region at a coarse scale
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`corresponds to one or more regions at each finer scale,” shown in Figure 4.
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`Ex.1006, 373.
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`Ex.1006, Fig. 4
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`
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`3.
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`Brady
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`Brady describes a method for identifying and tracking vehicles in a roadway
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`scene in real-time, as reflected in Figure 1. Ex.1007, 3:59-62.
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`Vehicles
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`Camera
`
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`Ex.1007, Fig. 1 (in part, annotated)
`
`
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`Brady stores identified vehicles and corresponding positional data in an
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`object list to aid in tracking. Ex.1007, 11:21-25. For example, Brady keeps “a
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`vehicle log 102 of all vehicles currently within the scene, including vehicles’
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`associated track histories, inertial history 104 of the scene…and potential future
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`track positions….” Ex.1007, 11:21-25.
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`4.
`
`Reasons to Combine Broggi-Huttenlocher-Brady
`
`a)
`
`Analogous Art
`
`Broggi, Huttenlocher, and Brady are analogous art to the ’805 patent. Broggi
`
`pertains to the same field of endeavor as the ’805 patent: image processing and the
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`detection of objects (e.g., vehicles) in images, including image processing in the
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`context of vehicle guidance. Ex.1001, 1:6-9; Ex.1005, 164 (Broggi presents
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`IPR2025-00342 Petition
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`“methods for sensing obstacles and vehicles”), 165, 166 (system functionalities
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`include “automatic following of the preceding vehicle, that requires the
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`localization and tracking of a target vehicle”), 170-172 (describing vehicle
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`detection). Broggi is reasonably pertinent to a particular problem addressed by the
`
`’805 patent, namely, path calculation to a destination based on image analysis.
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`Ex.1001, 3:13-22, 30-33; Ex.1005, 173-175, Fig. 21. Accordingly, Broggi is
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`analogous art to the ’805 patent. Ex.1003, ¶56.
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`Huttenlocher is analogous art in the same field of endeavor as the ’805
`
`patent: image processing and the detection of objects (e.g., vehicles) in images.
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`Ex.1006, 375, Figs. 2, 11 (image detection of a “personnel carrier”). Huttenlocher
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`is reasonably pertinent to particular problems addressed by the ’805 patent,
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`namely, object detection through image analysis and associated data
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`processing/storage. Ex.1001, 2:32-41; Ex.1006, 373 (“image is processed by an
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`edge detector,” “[a] hierarchy of curve segmentations can be obtained,” “the
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`hierarchy forms a tree of segments”), 374 (“[p]oints for use by the alignment
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`algorithm are obtained from the features” based on the types of segments stored in
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`the multi-scale segmentation tree). Accordingly, Huttenlocher is analogous art to
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`the ’805 patent. Ex.1003, ¶57.
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`Brady is analogous art in the same field of endeavor as the ’805 patent:
`
`
`
`image processing and the detection of objects (e.g., vehicles) in images, including
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`image processing to identify and “track objects within the roadway scene, such as a
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`vehicle[.]” Ex.1007, abstract. Brady is reasonably pertinent to a particular problem
`
`addressed by the ’805 patent, namely, vehicle detection through image analysis and
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`storing related information. Ex.1001, 2:48-52; Ex.1007, 11:21-25 (“keeping a
`
`vehicle log 102 of all vehicles currently within the scene, including vehicles’
`
`associated track histories, inertial history 104 of the scene…and potential future
`
`track positions”). Accordingly, Brady is analogous art to the ’805 patent. Ex.1003,
`
`¶58.
`
`b)
`
`Broggi-Huttenlocher
`
`A POSITA would have been motivated to implement Huttenlocher’s pattern
`
`matching technique utilized for object recognition as part of Broggi’s vehicle
`
`detection methods because doing so would have been the combination of prior art
`
`elements (Broggi’s vehicle detection using a “traditional pattern matching
`
`technique” and Huttenlocher’s known pattern matching technique) according to
`
`known methods to yield predictable results (using Huttenlocher’s known pattern
`
`matching technique as Broggi’s “traditional pattern matching technique” for
`
`vehicle detection). KSR Int’l v. Teleflex Inc., 550 U.S. 398, 416 (2007); Ex.1003,
`
`¶59.
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`Further, a POSITA would have been motivated to make the combination
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`
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`because Broggi contains an explicit teaching, suggestion, or motivation (calling for
`
`use of a “traditional pattern matching technique”) that would have led a POSITA to
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`modify Broggi to implement Huttenlocher’s known pattern matching technique.
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`Ex.1003, ¶60.
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`In the combination, Broggi implements Huttenlocher’s pattern matching
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`technique—that segments edges, stores edge segments in a multi-scale tree, and
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`analyzes the edge segments—as part of detecting the location of a preceding
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`vehicle. Ex.1003, ¶62. Huttenlocher’s pattern matching technique would be applied
`
`to the images obtained by Broggi to identify “possibly matching features”
`
`corresponding to the bottom corners and/or top of the preceding vehicle. See
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`Ex.1005, 170-171; Ex.1006, 370, 373-374; infra [1.4.1]-[1.4.3]; Ex.1003, ¶62. For
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`example, the image data may be processed to detect edges (in accordance with
`
`Broggi and/or Huttenlocher)2 and Huttenlocher’s pattern matching technique
`
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`2 Both Broggi and Huttenlocher disclose detecting edges in images. Ex.1005, 171;
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`Ex.1006, 373-374; Ex.1003, ¶61. As explained by Dr. Rodriguez, it would have
`
`been obvious to a POSITA that the Broggi-Huttenlocher combination would
`
`implement Broggi’s edge detection, Huttenlocher’s edge detection, or both
`
`Broggi’s edge detection and Huttenlocher’s edge detection. Ex.1003, ¶61. In this
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`would be applied to segment the edges, store edge segments in a multi-scale tree,
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`IPR2025-00342 Petition
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`and analyze the edge segments to detect the bottom corners and/or the top of the
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`preceding vehicle. A POSITA would have understood, based on Broggi’s
`
`description, that Huttenlocher’s pattern matching technique may be utilized for
`
`detecting the bottom corners, the top, or both the bottom corners and the top of the
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`preceding vehicle. Ex.1005, 170‑171; Ex.1003, ¶62. Once the preceding vehicle is
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`identified and a corresponding location is determined, Broggi automatically
`
`follows the preceding vehicle by calculating a steering angle for a desired path to
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`the location of the preceding vehicle and controls the steering of the vehicle
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`accordingly. See infra [1.3], [9.0]; Ex.1003, ¶62. Implementing Huttenlocher’s
`
`pattern matching technique would provide advantages for Broggi, including
`
`improved vehicle detection and efficient use of processing resources. Ex.1006, 379
`
`(“alignment can be performed with a small amount of information”); Ex.1003, ¶62.
`
`
`regard, using either Broggi’s edge detection or Huttenlocher’s edge detection
`
`would have been the simple substitution of one known element (Broggi’s or
`
`Huttenlocher’s edge detection) for another (the other of Huttenlocher’s or Broggi’s
`
`edge detection). Ex.1003, ¶61. Further, using both Broggi’s and Huttenlocher’s
`
`edge detection would be the combination of familiar elements according to known
`
`methods to yield predictable results. Ex.1003, ¶61.
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`A POSITA would have had a reasonable expectation of success in using
`
`
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`Huttenlocher’s pattern matching technique as Broggi’s “traditional pattern
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`matching technique” for vehicle detection because Huttenlocher provides an
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`explicit example of using its disclosed pattern matching technique to detect a
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`vehicle. Ex.1005, 171; Ex.1006, 375, Figs. 2, 11 (showing a “personnel carrier
`
`used in recognition,” and the “[l]ocal alignment of two views of a personnel
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`carrier.”); Ex.1003, ¶63.
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`Ex.1006, Fig. 11 (in part)
`
`c)
`
`Broggi-Huttenlocher-Brady
`
`
`
`A POSITA would have been motivated to modify the combined Broggi-
`
`Huttenlocher method discussed above to implement Brady’s teaching of keeping
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`an object list containing identified vehicle(s) with corresponding positional data (a
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`vehicle log) because doing so would have been the combination of prior art
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`elements (platooning, per Broggi-Huttenlocher, with Brady’s teaching of keeping a
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`vehicle log) according to known methods to yield predictable results (platooning,
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`per Broggi-Huttenlocher, using a vehicle log to keep track of a preceding vehicle
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`and associated position information). KSR, 550 U.S. at 416; Ex.1003, ¶64.
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`Broggi provides “an experimental autonomous vehicle equipped with vision
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`systems and automatic steering capability” for lane following and platooning,
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`including a processing system “based on a standard 450 MHz Pentium II
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`processor.” Ex.1005, 165. Despite Broggi’s focus on vehicle detection and tracking
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`for platooning, Broggi omits implementation details how the associated data is
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`processed and stored. Ex.1005, 170-172, 173 (noting that the described system “is
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`able to continuously capture images into a circular buffer in main memory,
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`therefore, not requiring a synchronization with the processing”); Ex.1003, ¶65.
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`Brady provides such implementation details in the same context of
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`“classifying and tracking vehicles” captured “in real-time[.]” Ex.1007, 3:59-62,
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`11:21-25; see Ex.1005, 172 (discussing “tracking an already found” vehicle). In
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`the combination, Broggi stores information regarding a preceding vehicle—
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`identified using Broggi-Huttenlocher—in a vehicle log, per Brady. Ex.1007, 11:21-
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`25. Consistent with the disclosures of Broggi and Brady, the vehicle log would
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`include an object list identifying the preceding vehicle and associated positional
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`information. Ex.1003, ¶66. Specifically, the positional information associated with
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`the preceding vehicle included in the object list would include a relative location of
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`IPR2025-00342 Petition
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`the preceding vehicle and an associated distance, in accordance with Broggi’s
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`platooning method. Ex.1007, 11:21-25 (a vehicle log includes “including vehicles’
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`associated track histories, inertial history 104 of the scene…and potential future
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`track positions”). See infra [1.4.4]; Ex.1005, 170 (“[T]he [preceding] vehicle is
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`localized and tracked using a single monocular image sequence; the correct
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`distance is refined thanks to stereo vision.”); Ex.1003, ¶66. Broggi’s method would
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`reference and update the object list over time (updating the positional information
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`to reflect the current location of the preceding vehicle and/or keep a log of past
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`locations) to perform the functions associated with platooning, including
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`determining a desired path and associated steering angle. Ex.1005, 173, Fig. 21;
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`Ex.1003, ¶66.
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`A POSITA would have looked at Brady’s teachings because they would
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`have advantageously provided a known mechanism for tracking vehicle positions
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`over time, which would improve Broggi’s platooning through accurate and
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`consistent tracking of the preceding vehicle positions used in the associated vehicle
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`path determinations, thereby improving the user experience during platooning.
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`Ex.1007, 11:21-25; Ex.1003, ¶67.
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`A POSITA would have had a reasonable expectation of success in
`
`combining Brady’s object list with the Broggi‑Huttenlocher combination because
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`Brady discloses that such an object list may be used in the context of identifying
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`and tracking vehicles in real-time, as performed in the Broggi‑Huttenlocher
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`combination. Ex.1007, 11:21-25, 1:8-11 (“tracking objects in images provided by
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`real-time video”); Ex.1005, Fig. 19, Table I; Ex.1003, ¶68. Thus, Brady provides
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`implementation details for maintaining and storing information for vehicle tracking
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`suitable for use with Broggi’s platooning method. Ex.1003, ¶68. Accordingly, a
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`POSITA would have had a reasonable expectation of success in implementing
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`Brady’s vehicle log to track preceding vehicles and associated positional
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`information as part of the combined Broggi-Huttenlocher method of platooning.
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`Ex.1003, ¶68.
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`5.
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`Claim 1.
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`[1.0] A method for assisting guidance of a motor vehicle on the basis of image
`data, the method comprising:
`
`Broggi discloses or renders obvious [1.0] because Broggi discloses
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`platooning, which provides assisted guidance and controls steering of a motor
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`vehicle to follow a preceding vehicle based on captured image data. Ex.1003,
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`¶¶69-73.
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`First, Broggi discloses a method for assisting guidance of a motor vehicle.
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`Broggi describes platooning, the “automatic following of the preceding
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`vehicle[.]” Ex.1005, 166; Ex.1003, ¶70.
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`Second, Broggi’s platooning is on the basis of image data. Broggi explains
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`
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`that “an autonomous vehicle must…detect vehicles and potential obstacles on its
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`path in order to perform…[p]latooning.” Ex.1005, 164. Broggi’s detection of
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`vehicles is performed using image data captured from cameras within the vehicle
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`as reflected in Figure 1 of Broggi, showing an example of an “autonomous
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`vehicle equipped with vision systems and automatic steering capability.”
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`Ex.1005, 165; Ex.1003, ¶71.
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`Ex.1005, Fig. 1 (in part, annotated)
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`
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`Broggi explains “[v]ehicles are localized and tracked using a single
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`monocular image sequence whilst a distance refinement is computed using stereo
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`vision.” Ex.1005, 164. “A mechanical device provides autonomous steering
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`capabilities.…The output fed by the vision system is used to turn the steering
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`wheel to maintain the vehicle inside the lane or follow the leading vehicle.”
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`Ex.1005, 166; Ex.1003, ¶72.
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`Thus, Broggi discloses or renders obvious a method for assisting guidance
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`of a motor vehicle (controlling steering of a motor vehicle to follow a preceding
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`vehicle) on the basis of image data (based on a monocular image sequence and/or
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`stereo vision). Ex.1003, ¶¶69-73.
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`[1.1] acquired image data3 using an imaging sensor from a surrounding field of
`the motor vehicle;
`
`Broggi discloses or renders obvious [1.1] because Broggi discloses image
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`data is captured using cameras mounted within the motor vehicle and captures the
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`environment around a motor vehicle during platooning. Ex.1003, ¶¶74-82.
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`First, Broggi renders obvious acquir[ing] image data using an imaging
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`sensor by disclosing acquiring image data using cameras within a motor vehicle.
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`Ex.1005, 165, Fig. 1 (showing an “autonomous vehicle equipped with vision
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`systems and automatic steering capability” that includes a pair of stereo cameras
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`for capturing a monocular image sequence and/or stereo vision); Ex.1003, ¶75.
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`3 Notwithstanding §112 issues, Petitioner interprets “acquired” as “acquiring” for
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`purposes of this Petition. Ex.1003, ¶74. Petitioner reserves the right to raise §112
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`challenges in other forums.
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`Broggi’s vehicle includes a “stereoscopic vision system consisting of two low-cost
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`synchronized cameras able to acquire pairs of grey level images
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`simultaneously.” Ex.1005, 165. Consistent with the ’805 patent, a POSITA would
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`have understood that Broggi’s cameras are an example of an imaging sensor,
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`because such cameras contain a sensor. Ex.1001, 2:56-57, Fig. 2; Ex.1003, ¶¶75-
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`76, 78-81.
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`Ex.1005, Fig. 1 (in part, annotated)
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`
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`Second, Broggi renders obvious that the acquired image data is from a
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`surrounding field of the motor vehicle because Broggi discloses that it captures
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`images using “passive sensors…to sense the surrounding environment.”
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`Ex.1005, 164-165, Fig. 2. The “surrounding environment” of Broggi is the same
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`surrounding field claimed in the ’805 patent. Ex.1003, ¶77.
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`Left Stereo Camera Image
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`Preceding Vehicle
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`Right Stereo Camera Image
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`Ex.1005, Fig 2 (annotated)
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`
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`In view of the ’805 patent specification, a POSITA would have understood
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`“a surrounding field of the motor vehicle” to include an area outside the motor
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`vehicle that may be captured by an imaging sensor/camera but does not require the
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`entire surrounding field of the motor vehicle (360-degree view). This is because
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`the’805 patent describes an image sensor aligned with the travel direction of a
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`vehicle. Ex.1001, 7:15-22, Figs. 2-3. Thus, the ’805 patent only captures the field
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`in front of the motor vehicle (i.e., less than a 360-degree view). Ex.1003, ¶¶78-81.
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`Ex.1001, Fig. 2 (annotated)
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`Cargo Door
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`Loading platform
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`Ex.1001, Fig. 3 (annotated)
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`Thus, Broggi discloses or renders obvious acquir[ing] image data (acquiring
`
`
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`image data using a monocular image sequence and/or stereo vision) using an
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`imaging sensor (acquired using one and/or both of the stereo cameras) from a
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`surrounding field of the motor vehicle (acquired images are from the surrounding
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`environment of the motor vehicle, e.g., the surrounding field in front of the vehicle
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`where a preceding vehicle of a platoon is positioned). Ex.1003, ¶¶74-82.
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`[1.2] extracting from the acquired image data positional parameters of at least
`one potential destination relative to the motor vehicle; and
`
`Broggi discloses or renders obvious [1.2] because Broggi renders obvious
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`extracting a location of a preceding vehicle in a platoon from the image data.
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`Ex.1003, ¶¶83-89. The location of the preceding vehicle represents a potential
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`destination of the motor vehicle. Ex.1003, ¶83. Broggi describes that a bounding
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`box defining a relative location of the preceding vehicle and an associated distance
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`are extracted from images acquired using a monocular image sequence and/or
`
`stereo vision to determine the location of a preceding vehicle relative to the motor
`
`vehicle. Ex.1003, ¶83.
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`As discussed in [1.1], Broggi acquires images using a monocular image
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`sequence and/or stereo vision that are used in platooning, including “estimat[ing
`
`the] position of the preceding vehicle.” Ex.1005, 164-165; Ex.1003, ¶84. Broggi
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`explains that the motor vehicle “determine[s] its position with respect to the lane,
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`to compute road geometry, to detect generic obstacles on the path, and to localize
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`a leading vehicle” using images acquired by the vehicle’s cameras. Ex.1005, 165;
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`Ex.1003, ¶84.
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`First, Broggi extract[s]…positional parameters [from the acquired image
`
`data] by extracting a relative location and associated distance of the preceding
`
`vehicle from the acquired image data as part of platooning. Ex.1005, 170 (“[T]he
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`[preceding] vehicle is localized and tracked using a single monocular image
`
`sequence; the correct distance is refined thanks to stereo vision.”)4; Ex.1003, ¶85.
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`This extraction is performed on image data through the analysis of “a specific
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`region of the image” acquired using a monocular image sequence and/or stereo
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`vision. Ex.1005, 170, 171 (describing “the search area” for each image). The
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`relative location of the preceding vehicle is represented by a bounding box.
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`Ex.1005, 171. An example of a bounding box and corresponding preceding vehicle
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`is shown in Fig. 16, while an example of the distance refinement is shown in Fig.
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`17. Ex.1005, 172; Ex.1003, ¶85.
`
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`4 Broggi’s teaching is similar in scope to the ’805 patent, which describes relative
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`position data, not precise coordinates. Ex.1001, 3:13-22 (describing “relative
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`positional data”), 6:8-13 (“object…whose position relative to the imaging sensor
`
`is known”); Ex.1003, ¶85.
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`Bounding Box
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`Preceding Vehicle
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`Ex.1005, Fig. 16 (annotated)
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`Ex.1005, Fig. 17
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`The location of the bounding box within the image (defining a relative
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`
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`location of the preceding vehicle) is used to compute the distance to the preceding
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`vehicle relative to the vehicle. Ex.1005, 172 (“the offset of the bounding boxes
`
`containing the vehicle, measured in both images, is used to compute the vehicle
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`distance.”); Ex.1003, ¶¶85-87. Accordingly, Broggi renders obvious extracting
`
`from the acquired image data positional parameters including (1) the location of
`
`the preceding vehicle relative to the motor vehicle, as identified by the bounding
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`box; and (2) the distance to the preceding vehicle. Ex.1003, ¶¶85-87.
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`Second, th