Randomized Query Processing in Robot Motion Planning.

Abstract

The subject of this paper is the analysis of a randomized preprocessing scheme that has been used for query processing in robot motion planning. The attractiveness of the scheme stems from its general applicability to virtually any motion planning problem, and its empirically observed success. In this paper we initiate a theoretical basis for explaining this empirical success. Under a simple assumption about the configuration space, we show that it is possible to perform a preprocessing step following which queries can be answered quickly. En route, we pose and give solutions to related problems on graph connectivity in the evasiveness model, and art gallery theorems.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1994
Accession Number
ADA326821

Entities

People

  • Jean-claude Latombe
  • Lydia Kavraki
  • P. Raghavan
  • Rajeew Motwani

Organizations

  • Stanford University

Tags

Communities of Interest

  • Air Platforms
  • Autonomy

DTIC Thesaurus Topics

  • Algorithms
  • Classification
  • Computer Science
  • Motion Planning
  • Preprocessing
  • Probability
  • Robotics
  • Robots
  • Sampling
  • Security
  • Statistical Samples
  • Statistical Sampling
  • Theorems
  • Universities

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Computer Vision.
  • Graph Algorithms and Convex Optimization.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Information Retrieval
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Space
  • Space - Spacecraft Maneuvers