Remote Imagery for Unmanned Ground Vehicles (RIUGV)

摘要

The combination of high-resolution multi-spectral satellite imagery and advanced COTS object-oriented image processing software provides for an automated terrain feature extraction and classification capability. This information, along with elevation data, infrared imagery, a vehicle mobility model and various meta-data (local weather reports, Zobler Soil map, etc...), is fed into automated path planning software to provide a stand-alone ability to generate rapidly updateable dynamic mobility maps for Manned or Unmanned Ground Vehicles (MGVs or UGVs). These polygon based mobility maps can reside on an individual platform or a tactical network. When new information is available, change files are generated and ingested into existing mobility maps based on user selected criteria. Bandwidth concerns are mitigated by the use of shape files for the representation of the data (e.g. each object in the scene is represented by a shape file and thus can be transmitted individually). User input (desired level of stealth, required time of arrival, etc...) determines the priority in which objects are tagged for updates. This technology was tested at Fort Knox, Kentucky October 11th - 15th 2004. Satellite imagery was acquired in a near-real-time fashion for the selected test site. Portions of the resulting geo-rectified image were compared with surveyed range locations to assess the accuracy of the approach. The derived UGV Path Plans were ingested into a Stryker UGV and the routes were autonomously traversed. This paper will detail the feasibility of this approach based of the results of this testing.