An architecture for object modeling and recognition for an autonomous land vehicle is presented. Examples of objects of interest include terrain features, fields, roads, horizon features, trees, etc. The architecture is organized around a set of data bases for generic object models and perceptual structures, temporary memory for the instantiation of object and relational hypotheses, and a long term memory for storing stable hypotheses that are affixed to the terrain representation. Multiple inference processes operate over these databases. Researchers describe these particular components: the perpetual structure database, the grouping processes that operate over this, schemas, and the term terrain database. A processing example that matches predictions from the long term terrain model to imagery, extracts significant perceptual structures for consideration as potential landmarks, and extracts a relational structure to update the long term terrain database is given.

  • Supplemental Notes:
    • Paper in Jet Propulsion Lab., Californis Inst. of Tech. Proceedings of the Workshop on Space Telerobotics, volume 1, pp 313-336
  • Corporate Authors:

    Advanced Decision Systems

    Mountain View, CA  United States 
  • Authors:
    • Lawton, D T
    • Levitt, T S
    • Mcconnell, C C
    • Nelson, P C
  • Publication Date: 1987-7

Media Info

  • Pagination: 24 p.

Subject/Index Terms

Filing Info

  • Accession Number: 00494053
  • Record Type: Publication
  • Source Agency: National Technical Information Service
  • Files: TRIS
  • Created Date: Apr 30 1990 12:00AM