{
  "$type": "site.standard.document",
  "description": "A method for generating training data for a machine learning model. The method includes: providing LIDAR point clouds, each of which is assigned to a point in time of a plurality of successive points in time, wherein each point of each LIDAR point cloud represents a particular object class of a…",
  "path": "/patents/1381388",
  "publishedAt": "2026-04-23T00:00:00.000Z",
  "site": "at://did:plc:oql6ds5vnff4ugar6rruliwd/site.standard.publication/3mn3ohu7oxx5w",
  "tags": [
    "G01S17/931",
    "Robert Bosch GmbH"
  ],
  "textContent": "A method for generating training data for a machine learning model. The method includes: providing LIDAR point clouds, each of which is assigned to a point in time of a plurality of successive points in time, wherein each point of each LIDAR point cloud represents a particular object class of a plurality of object classes; for each LIDAR point cloud: ascertaining a transmission grid map in spherical coordinate space, wherein each voxel of the transmission grid map indicates how many rays pass through the voxel before they are reflected at a point in the LIDAR point cloud; ascertaining a reference transmission grid map in Cartesian coordinate space assigned to a reference point in time of the plurality of points in time; for each of the plurality of object classes: for each LIDAR point cloud, ascertaining a reflection grid map associated with the object class.",
  "title": "METHOD FOR GENERATING TRAINING DATA FOR A MACHINE LEARNING MODEL"
}