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Proceedings Paper

Region Based Route Planning: Multi-Abstraction Route Planning Based On Intermediate Level Vision Processing
Author(s): Rajkumar S. Doshi; Raymond Lam; James E. White
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Paper Abstract

The Region Based Route Planner performs intermediate-level and high-level processing on vision data to organize the image into more meaningful higher-level topological representations. A variety of representations are employed at appropriate stages in the route plan-ning process. A variety of abstractions are used for the purposes of problem reduction and application of multiple criteria at different phases during the navigation planning process. The Region Based Route Planner operates in terrain scenarios where some or most of the terrain is occluded. The Region Based Route Planner operates without any priori maps. The route planner uses two dimensional representations and utilizes gradient and roughness information. The implementation described here is being tested on the JPL Robotic Vehicle. The Region Based Route Planner operates in two phases. In the first phase, the terrain map is segmented to derive global information about various features in it. The next phase is the actual route planning phase. The route is planned with increasing amounts of detail by successive refinement. This phase has three abstrac-tions. In the first abstraction, the planner analyses high level information and so a coarse, region-to-region plan is produced. The second abstraction produces a list of pairs of entry and exit waypoints for only these selected regions. In the last abstraction, for every pair of these waypoints, a local route planner is invoked. This planner finds a detailed point-to-point path by searching only within the boundaries of these relatively small regions.

Paper Details

Date Published: 5 January 1989
PDF: 16 pages
Proc. SPIE 1003, Sensor Fusion: Spatial Reasoning and Scene Interpretation, (5 January 1989); doi: 10.1117/12.948961
Show Author Affiliations
Rajkumar S. Doshi, California Institute Of Technology (United States)
Raymond Lam, California Institute Of Technology (United States)
James E. White, California Institute Of Technology (United States)

Published in SPIE Proceedings Vol. 1003:
Sensor Fusion: Spatial Reasoning and Scene Interpretation
Paul S. Schenker, Editor(s)

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