Dynamic World Modeling for an Intelligent Mobile Robot Using a Rotating Ultra-Sonic Ranging Device.

Abstract

A system which performs task-oriented navigation for an intelligent mobile robot is described in this paper. This navigation system is based on a dynamically maintained model of the local environment, called the 'Composite Local Model'. The Composite Local Model integrates information from a rotating sonar sensor, the robot's touch sensor and a pre-learned Global Model as the robot moves through its environment. Techniques are described for constructing a line segment description of the most recent sensor scan (the Sensor Model) and for integrating such descriptions to build up a model of the immediate environment (the Composite Local Model). Model integration is based on a process of reinforcing the confidence in the consistent information while decaying the confidence in inconsistent information. The estimated position of the robot is corrected by the difference in position between observed sensor signals and the corresponding symbols in the Composite Local Model. This system is useful for navigation in a finite, pre-learned domain such as a house, office, or factory.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1984
Accession Number
ADA149979

Entities

People

  • J. L. Crowley

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Automatic
  • Cartesian Coordinates
  • Collision Avoidance
  • Coordinate Systems
  • Equations
  • Geometry
  • Learning
  • Motion Planning
  • Navigation
  • Orientation (Direction)
  • Position Finding
  • Range Finding
  • Robotics
  • Robots
  • Sequences
  • Sonar Ranging
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Computational Modeling and Simulation
  • Positioning, Navigation, and Timing (PNT) Technology.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Bayesian Inference
  • Autonomy