Planning with Pinch Points

Abstract

We describe a heuristic search algorithm for generating optimal plans in a new class of decision problem, characterized by the incorporation of hidden state. The approach exploits the nature of the hidden state to reduce the state space by orders of magnitude. It then interleaves AO*-type heuristic expansion of the reduced space with forwards and backwards propagation phases to produce a solution in a fraction of the time required by other techniques. Results are provided on an outdoor path planning application.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2004
Accession Number
ADA528745

Entities

People

  • Anthony Stentz
  • Dave Ferguson
  • Sebastian Thrun

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Autonomy
  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Autonomous Navigation
  • Computations
  • Cost Estimates
  • Costs
  • Environment
  • Iterations
  • Low Resolution
  • Motion Planning
  • Navigation
  • Probability
  • Probability Distributions
  • Robot Navigation
  • Robotics
  • Robots
  • Standards

Readers

  • Computer Vision.
  • Operations Research
  • Pulsed Power and Plasma Physics.

Technology Areas

  • Space
  • Space - Space Objects