{
  "patent_number": "US 10733420",
  "country": "US",
  "title": "How Self-Driving Cars Find Clear Paths Between Objects",
  "original_title": "Systems and methods for free space inference to break apart clustered objects in vehicle perception systems",
  "summary": "This patent describes a method for vehicles, especially self-driving ones, to use lidar data and a 3D grid to precisely identify open spaces between obstacles, helping them navigate safely.",
  "what_it_does": "The patent details a system for a vehicle to find clear paths between objects using a lidar system and a 3D map called a \"voxel grid.\" First, the vehicle's computer retrieves this voxel grid, which is like a stack of tiny cubes representing the space around the vehicle (Claim 1). Lidar beams are then traced through these cubes. Each cube, or \"voxel,\" gets a score based on whether a lidar beam passed through it (a \"first characteristic\" like 'clear'), didn't pass through (a \"second characteristic\" like 'unknown'), or stopped at it (a \"third characteristic\" like 'occupied') (Claims 1, 4-5). The system then looks at vertical \"columns\" of these cubes and finds the longest continuous sequence of cubes that maximizes a score, indicating the most likely clear path (Claim 1). For example, if a column of voxels has clear spaces above occupied spaces, the system identifies the clear section. Finally, based on the length and height (elevation) of this clear section, each column is classified with a \"free space level\" and presented as an image (Claim 1), helping the vehicle understand where it can drive.",
  "what_it_does_not_cover": [
    "Does not cover systems that identify free space using only 2D data without a 3D voxel grid around the vehicle.",
    "Does not cover methods that classify free space without specifically identifying a 'max subarray' of contiguous elements in a column.",
    "Does not cover systems that don't assign scores to voxels based on lidar beam interaction (e.g., clear, unknown, occupied) within the voxel grid.",
    "Does not cover methods that classify free space without considering both the identified subarray length for the column and the identified elevation for the column.",
    "Does not cover systems that rely solely on radar or camera data for free space identification without using lidar beams as described."
  ],
  "filed": "2017-11-21",
  "granted": "2020-08-04",
  "expires": "2037-11-21",
  "status": "active",
  "holder": "GM Global Technology Operations",
  "holder_url": "https://patentbrief.org/company/gm-global-technology-operations",
  "inventors": [
    {
      "name": "Mark Liu",
      "url": "https://patentbrief.org/inventor/mark-liu"
    }
  ],
  "times_cited": 1,
  "tags": [
    "automotive",
    "ai_ml",
    "software",
    "telecommunications"
  ],
  "abstract": "Systems and method are provided for identifying free space between objects. The method includes retrieving, by a processor, a voxel grid around the vehicle wherein the voxel grid has a plurality of columns. The method further includes tracing, by the processor, lidar beams from a lidar system on the vehicle through the voxel grid, identifying, by the processor, a max subarray for each column in the voxel grid, classifying, by the processor, each column with a free space level, and outputting, by the processor, the classified columns as an image.",
  "url": "https://patentbrief.org/patent/us/10733420/systems-and-methods-for-free-space-inference-to-break-apart-clustered-objects-in",
  "markdown_url": "https://patentbrief.org/patent/us/10733420/systems-and-methods-for-free-space-inference-to-break-apart-clustered-objects-in/md",
  "google_patents_url": "https://patents.google.com/patent/US10733420",
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}