Robot Motion Planning with Uncertainty in Control and Sensing.

Abstract

In this paper, we consider the problem of planning motion strategies in the presence of uncertainty in both control and sensing for simple robots described in a two dimensional configuration space. We consider the preimage backchaining approach to this problem. which was first proposed by Lozano-Perez. Mason and Taylor (1984). Although attractive, the approach raises several difficult computational issues. One of them, which is directly addressed in this paper. is preimage computation. We describe two practical methods for computing preimages, which we call backprojection from sticking edges and backprojection from goal kernel. Also discussed non-implemented improvements of this planner and additional results.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1989
Accession Number
ADA323613

Entities

People

  • A. Lazanas
  • J. C. Latombe
  • S. Shekhar

Organizations

  • Stanford University

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Applied Mathematics
  • Artificial Intelligence
  • Collision Avoidance
  • Commerce
  • Computer Programming
  • Computer Science
  • Coordinate Systems
  • Electrical Engineering
  • Engineering
  • Geometry
  • Lisp Programming Language
  • Mechanical Engineering
  • Motion Planning
  • Robots
  • Two Dimensional

Readers

  • Calculus or Mathematical Analysis
  • Graph Algorithms and Convex Optimization.
  • Robotics and Automation.

Technology Areas

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