Tracking vehicles in a warehouse environment

{
  "publication_number": "US2019370567A1",
  "country": "US",
  "kind": "A1",
  "title": "Tracking vehicles in a warehouse environment",
  "abstract": "This specification generally discloses technology for tracking vehicle positions in a warehouse environment. A system receives stereoscopic image data from a camera on a forklift, in some implementations. The system recognizes an object that is represented in the stereoscopic image data, identifies a representation of the recognized object in a spatial model that identifies, for each of a plurality of objects in an environment, a corresponding location of the object in the environment, determines the location of the recognized object in the environment, determines a relative position between the forklift and the recognized object, based on a portion of the received stereoscopic image data that represents the recognized object, and determines a location of the forklift in the environment, based on the determined location of the recognized object in the environment, and the determined relative position between the forklift and the recognized object.",
  "claims": [
    "1. A computer-implemented method, comprising: receiving stereoscopic image data that is based on at least one stereoscopic image that was captured by a stereoscopic camera that is affixed to a forklift; recognizing an object that is represented in the stereoscopic image data; identifying a representation of the recognized object in a spatial model that identifies, for each of a plurality of objects in an environment, a corresponding location of the object in the environment; determining the location of the recognized object in the environment, as indicated by the spatial model; determining a relative position between the forklift and the recognized object, based on a portion of the received stereoscopic image data that represents the recognized object; and determining a location of the forklift in the environment, based on the determined location of the recognized object in the environment, and the determined relative position between the forklift and the recognized object. 2. The computer-implemented method of claim 1, wherein the stereoscopic image data is based on a series of stereoscopic images received in real time as the images are captured by the stereoscopic camera, each stereoscopic image being captured at a fixed time interval. 3. The computer-implemented method of claim 1, further comprising determining that the recognized object is associated with a fixed location in the environment, including determining that the object's location has not changed for a predetermined length of time. 4. The computer-implemented method of claim 1, further comprising determining that the recognized object is associated with a fixed location in the environment, including determining that the recognized object has been designated as a fixed location object. 5. The computer-implemented method of claim 4, further comprising: while the forklift is within a predefined area associated with the recognized object, determining locations of further recognized objects in the environment includes processing only a portion of the spatial model that corresponds to the predefined area. 6. The computer-implemented method of claim 1, further comprising: receiving, from at least one environmental sensor other than the stereoscopic camera, an environmental signal, wherein determining the location of the forklift in the environment is based at least in part on the environmental signal. 7. A system, comprising: a stereoscopic camera affixed to a forklift; and a computing device communicatively coupled to the stereoscopic camera, the computing device configured to perform operations comprising: receiving stereoscopic image data that is based on at least one stereoscopic image that was captured by a stereoscopic camera that is affixed to a forklift; recognizing an object that is represented in the stereoscopic image data; identifying a representation of the recognized object in a spatial model that identifies, for each of a plurality of objects in an environment, a corresponding location of the object in the environment; determining the location of the recognized object in the environment, as indicated by the spatial model; determining a relative position between the forklift and the recognized object, based on a portion of the received stereoscopic image data that represents the recognized object; and determining a location of the forklift in the environment, based on the determined location of the recognized object in the environment, and the determined relative position between the forklift and the recognized object. 8. The system of claim 7, wherein the stereoscopic image data is based on a series of stereoscopic images received in real time as the images are captured by the stereoscopic camera, each stereoscopic image being captured at a fixed time interval. 9. The system of claim 7, wherein the stereoscopic camera is affixed to an overhead guard of the forklift such that the stereoscopic camera points behind the forklift. 10. The system of claim 9, wherein the stereoscopic camera includes a lens heater. 11. A computer-implemented method comprising: recognizing a first object that is represented in first stereoscopic image data based on one or more stereoscopic images received from a first stereoscopic camera that has been affixed to a vehicle; recognizing a second object that is represented in second stereoscopic image data based on one or more stereoscopic images received from a second stereoscopic camera that has been affixed to the vehicle; identifying respective representations of the first object and the second object in a spatial model that tracks, for each of a plurality of objects, a corresponding location in an environment and a level of confidence that the corresponding location is the object's actual location; determining a first location of the first object in the environment and a first level of confidence that the first location is the first object's actual location, according to the spatial model; determining a second location of the second object in the environment and a second level of confidence that the second location is the second object's actual location, according to the spatial model; and in response to determining that the first level of confidence for the first object's location is greater than the second level of confidence for the second object's location: determining a relative position between the vehicle and the first object, based on a portion of the first stereoscopic image data that represents the first object; and determining a location of the vehicle in the environment, based on the determined first location of the first object in the environment, and the determined relative position between the vehicle and the first object. 12. The computer-implemented method of claim 11, wherein a level of confidence that a corresponding location is an object's actual location is proportional to an amount of time that the object has been at the corresponding location, according to the spatial model. 13. The computer-implemented method of claim 11, wherein a level of confidence that a corresponding location is an object's actual location is a highest level of confidence when the object has been designated as a fixed location object. 14. The computer-implemented method of claim 11, further comprising: receiving, from at least one environmental sensor other than the stereoscopic camera, an environmental signal, wherein determining the location of the vehicle within the environment is based at least in part on the environmental signal. 15 - 18. (canceled)"
  ],
  "cpc": [
    "G06Q 10/0833",
    "G01S 3/00",
    "G01S 5/16",
    "G06K 9/00771",
    "G06K 9/00805",
    "G06Q 10/08",
    "G06Q 10/087",
    "G06T 2207/10012",
    "G06T 2207/30236",
    "G06T 2207/30261",
    "G06T 7/74",
    "G06T 7/75",
    "G06V 20/52",
    "G06V 20/54",
    "G06V 20/56",
    "G06V 20/58",
    "H04N 13/204"
  ],
  "assignees": [
    "LINEAGE LOGISTICS LLC"
  ],
  "filing_date": "2019-02-15",
  "publication_date": "2019-12-05",
  "priority_date": "2018-05-30",
  "application_number": "US-201916277338-A",
  "family_id": "65811888"
}