Planning with Map Uncertainty

Abstract

We describe an efficient method for planning in environments for which prior maps are plagued with uncertainty. Our approach processes the map to determine key areas whose uncertainty is crucial to the planning task. It then incorporates the uncertainty associated with these areas using the recently developed PAO* algorithm to produce a fast, robust solution to the original planning task.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 2004
Accession Number
ADA529036

Entities

People

  • Anthony Stentz
  • Dave Ferguson

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Computations
  • Cost Estimates
  • Costs
  • Environment
  • Extraction
  • Information Operations
  • Low Resolution
  • Mathematics
  • Military Research
  • Models
  • Probability
  • Probability Distributions
  • Robots
  • Terrain Models
  • Uncertainty

Readers

  • Artificial Intelligence
  • Computer Vision.
  • Systems Analysis and Design