{
  "$type": "site.standard.document",
  "description": "A computer-implemented method is presented for determining sampling rate for at least one of a camera and a receiver of a global navigation satellite system deployed in an autonomous vehicle. A Kalman filter is used for predicting a local sampling rate for the camera and a global sampling rate for…",
  "path": "/patents/1363946",
  "publishedAt": "2024-05-23T00:00:00.000Z",
  "site": "at://did:plc:oql6ds5vnff4ugar6rruliwd/site.standard.publication/3mn3ohu7oxx5w",
  "tags": [
    "G01C21/1656",
    "THE REGENTS OF THE UNIVERSITY OF MICHIGAN"
  ],
  "textContent": "A computer-implemented method is presented for determining sampling rate for at least one of a camera and a receiver of a global navigation satellite system deployed in an autonomous vehicle. A Kalman filter is used for predicting a local sampling rate for the camera and a global sampling rate for the receiver in the global navigation satellite system. The method includes: retrieving length of the lane being traversed by the autonomous vehicle from a graph, where nodes of the graph represent intersection in a road network and edges of the graph represent paths in the road network; measuring speed of the autonomous vehicle as it traverses the lane; estimating the local sampling rate and the global sampling rate using the measured speed and the Kalman filter; and capturing, by the camera, images in accordance with the local sampling rate estimated by the Kalman filter.",
  "title": "Energy Efficient Sampling For Last-Mile Delivery Systems"
}