{
  "$type": "site.standard.document",
  "description": "Certain aspects of the present disclosure provide techniques for performing trajectory planning for an object, including: obtaining an ST scene representing 1) a displacement of one or more agents over time with respect to a reference point corresponding to a current position of the object and 2) a…",
  "path": "/patents/1378261",
  "publishedAt": "2026-01-29T00:00:00.000Z",
  "site": "at://did:plc:oql6ds5vnff4ugar6rruliwd/site.standard.publication/3mn3ohu7oxx5w",
  "tags": [
    "B60W60/00276",
    "QUALCOMM Incorporated"
  ],
  "textContent": "Certain aspects of the present disclosure provide techniques for performing trajectory planning for an object, including: obtaining an ST scene representing 1) a displacement of one or more agents over time with respect to a reference point corresponding to a current position of the object and 2) a target location of the object; inputting the ST scene into a first machine learning model; outputting, by the first machine learning model, based on the input ST scene, a first target trajectory for the object to follow to occupy the target location; sending the first target trajectory to a second machine learning model; and obtaining, from the second machine learning model, a second target trajectory for the object to follow to occupy the target location.",
  "title": "STATION-TIME SCENE REPRESENTATION FOR MACHINE LEARNING (ML)-BASED PLANNING"
}