Waymo was granted a patent for detecting lidar sensor fouling.

{
  "signal_id": "1fa207a5-45a3-5c87-b14b-ab83f491d204",
  "signal_type": "patents-company",
  "signal_subtype": "patentGrant",
  "detected_at": "2026-09-30T17:10:39+00:00",
  "company": {
    "name": "Waymo",
    "domain": "waymo.com"
  },
  "data": {
    "cpc": [
      {
        "code": "G01S 7/497",
        "label": "Radio direction-finding, navigation, ranging (radar/lidar/sonar)"
      },
      {
        "code": "B60S 1/56"
      },
      {
        "code": "G01S 17/931",
        "label": "Radio direction-finding, navigation, ranging (radar/lidar/sonar)"
      },
      {
        "code": "G01S 2007/4977",
        "label": "Radio direction-finding, navigation, ranging (radar/lidar/sonar)"
      }
    ],
    "tags": [
      "Intellectual Property",
      "Research & Development",
      "Autonomous Technology",
      "Automotive"
    ],
    "detail": "In September 2026 Waymo patented a way to identify contamination on lidar apertures, supporting reliable perception for autonomous vehicles on the road.",
    "summary": "Waymo was granted a patent for detecting lidar sensor fouling.",
    "event_at": "2026-09-29",
    "inventors": [
      {
        "name": "Jingyuan Linda Zhang",
        "status": "resolved",
        "is_primary": true,
        "linkedin_url": "https://www.linkedin.com/in/jingyuan-linda-zhang"
      },
      {
        "name": "Caner Onal",
        "status": "resolved",
        "is_primary": false,
        "linkedin_url": "https://www.linkedin.com/in/caneronal"
      }
    ],
    "tech_area": "radar / lidar / sensing",
    "event_kind": "grant_date",
    "grant_date": "2026-09-29",
    "source_url": "https://patents.google.com/patent/US12748199",
    "cpc_primary": {
      "code": "G01S 7/497",
      "label": "Radio direction-finding, navigation, ranging (radar/lidar/sonar)"
    },
    "patent_title": "Methods for detecting lidar aperture fouling",
    "patent_number": "US12748199",
    "uspto_assignee": "Waymo LLC",
    "patent_abstract": "An example method includes receiving point cloud information about a field of view of a lidar system. The point cloud information includes spatiotemporal and amplitude information about return light received. The method also includes determining, based on the point cloud information, a set of bright light returns from at least one highly reflective object. The bright light returns include return light having an amplitude above a photon threshold and a corresponding bright light return range. The method yet further includes determining, based on the point cloud information, a set of crosstalk returns. The crosstalk returns include return light having a corresponding crosstalk return range. The method includes adjusting, based on a normalized number of crosstalk returns, at least one of: a cleaning system, an operating mode of a lidar system, or an operating mode of a vehicle.",
    "precision_class": "structural",
    "invention_explanation": "A method that examines lidar point-cloud returns, spotting unusually bright reflections and their ranges as clues that the sensor opening is dirty or obstructed.",
    "technologies_mentioned": [
      "lidar",
      "point-cloud processing",
      "autonomous vehicle sensing"
    ]
  }
}

curl https://signals.autobound.ai/v1/signals/1fa207a5-45a3-5c87-b14b-ab83f491d204 \
  -H "X-API-KEY: $AUTOBOUND_API_KEY"

curl -X POST https://signals.autobound.ai/v1/companies/enrich \
  -H "X-API-KEY: $AUTOBOUND_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"domain":"waymo.com","limit":20}'