Boeing was granted a patent for neural-network aircraft pose estimation.

{
  "signal_id": "24e8921d-3438-56ee-a217-ee628a5a3669",
  "signal_type": "patents-company",
  "signal_subtype": "patentGrant",
  "detected_at": "2026-10-14T15:57:19+00:00",
  "company": {
    "name": "Boeing",
    "domain": "boeing.com"
  },
  "data": {
    "cpc": [
      {
        "code": "G06T 7/70",
        "label": "Image data processing or generation, in general"
      },
      {
        "code": "G06T 7/593",
        "label": "Image data processing or generation, in general"
      },
      {
        "code": "G06T 2207/20081",
        "label": "Image data processing or generation, in general"
      },
      {
        "code": "G06T 2207/20084",
        "label": "Image data processing or generation, in general"
      }
    ],
    "tags": [
      "Intellectual Property",
      "Research & Development",
      "Artificial Intelligence",
      "Machine Learning",
      "Automotive"
    ],
    "detail": "In October 2026 Boeing patented RGB-D image analysis for supporting aerial refueling, helping tanker aircraft track receiving aircraft in flight.",
    "summary": "Boeing was granted a patent for neural-network aircraft pose estimation.",
    "event_at": "2026-10-13",
    "inventors": [
      {
        "name": "Tameez Latib",
        "status": "resolved",
        "is_primary": true,
        "linkedin_url": "https://www.linkedin.com/in/tameez-latib"
      },
      {
        "name": "Leon Nguyen",
        "status": "unresolved",
        "is_primary": false
      },
      {
        "name": "Haden Smith",
        "status": "unresolved",
        "is_primary": false
      },
      {
        "name": "Fan Hin Hung",
        "status": "resolved",
        "is_primary": false,
        "linkedin_url": "https://www.linkedin.com/in/fan-hin-hung-9a705591"
      },
      {
        "name": "Deepak Khosla",
        "status": "resolved",
        "is_primary": false,
        "linkedin_url": "https://www.linkedin.com/in/khoslahrl"
      }
    ],
    "tech_area": "image processing / graphics",
    "event_kind": "grant_date",
    "grant_date": "2026-10-13",
    "source_url": "https://patents.google.com/patent/US12762726",
    "cpc_primary": {
      "code": "G06T 7/70",
      "label": "Image data processing or generation, in general"
    },
    "patent_title": "RGBD-based neural network and training for pose estimation",
    "patent_number": "US12762726",
    "uspto_assignee": "The Boeing Company",
    "patent_abstract": "Disclosed herein are methods, systems, and aircraft for performing image analysis for aiding refueling operations. A tanker aircraft includes a camera system configured to generate a two-dimensional (2D) image of a receiving aircraft and a depth image of the receiving aircraft, a processor, and non-transitory computer readable storage media storing code. The code is executable by the processor to perform operations including detecting the receiving aircraft within the 2D image based on 2D image values, determining 2D keypoints of the receiving aircraft located within the 2D image based on the depth image, the 2D image values, and a previously determined keypoint model, determining a 6 degree-of-freedom (6DOF) pose using the 2D keypoints and corresponding three-dimensional (3D) keypoints, and outputting a position of at least a component of the receiving aircraft based on the 6DOF pose.",
    "precision_class": "structural",
    "invention_explanation": "A system combines ordinary camera images with depth data and neural-network analysis to determine another aircraft’s position and orientation during refueling.",
    "technologies_mentioned": [
      "computer vision",
      "neural networks",
      "RGB-D imaging",
      "aerial refueling"
    ]
  }
}

curl https://signals.autobound.ai/v1/signals/24e8921d-3438-56ee-a217-ee628a5a3669 \
  -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":"boeing.com","limit":20}'