An automatic navigation system for vision guided vehicles using a double heuristic and a finite state machine

Koon Yu Fok, Mansur R. Kabuka

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

A navigation system for automatic vision-guided vehicles which uses an efficient double heuristic search algorithm for path planning is presented. It is capable of avoiding unknown obstacles and recovering from unidentifiable locations. A linked list representation of the path network database makes the implementation feasible in any high-level language and renders it suitable for real-time application. Extensive simulated experiments have been conducted to verify the validity of the proposed algorithms. The combination of the techniques of robot navigation in unexplored terrain and the global map method proved to be a valid technique for automated guided vehicle (AGV) guidance. A learning mechanism is used in the AGV by updating the path network during navigation. Simulated results supported all the theoretically expected conclusions, since the robot planned its path correctly between the requested nodes and maneuvered its way around the obstacles. Overall, the results were very encouraging. The AGV even recovered from lost and unidentifiable locations.

Original languageEnglish
Pages (from-to)181-189
Number of pages9
JournalIEEE Transactions on Robotics and Automation
Volume7
Issue number1
DOIs
StatePublished - Feb 1 1991

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Finite automata
Navigation systems
Navigation
Robots
High level languages
Motion planning
Experiments

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

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