An Adaptive Vision-Based Approach to Decentralized Formation Control

Abstract

In considering the problem of formation control in the deployment of intelligent munitions, it would be highly desirable, both from a mission and a cost perspective, to limit the information that is transmitted between vehicles in formation. In a previous paper, we proposed an adaptive output feedback approach to address this problem. Adaptive formation controllers were designed that allow each vehicle in formation to maintain separation and relative orientation with respect to neighboring vehicles, while avoiding obstacles. In this paper, we consider a modification to the adaptive control law that enables each vehicle in a leader-follower formation to track line-of-sight (LOS) range with respect to two or more neighboring vehicles with zero steady-state error. We also propose a coordination scheme in which each vehicle tracks LOS range to up to two nearest vehicles while simultaneously navigating towards a common set of waypoints. This coordination scheme does not require a unique leader for the formation, increasing robustness of the formation. As our results show, such leaderless formations can perform maneuvers like splitting to go around obstacles, rejoining after negotiating the obstacles, and changing into line-shaped formation in order to move through narrow corridors.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2004
Accession Number
ADA509400

Entities

People

  • Anthony J. Calise
  • Johnny H. Evers
  • Ramachandra Sattigeri

Organizations

  • Georgia Tech

Tags

Communities of Interest

  • Air Platforms
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Aircrafts
  • Collision Avoidance
  • Computer Graphics
  • Control Systems
  • Engineering
  • Equations
  • Guidance
  • Inertial Measurement Units
  • Law
  • Multiple Input Multiple Output
  • Navigation
  • Neural Networks
  • Simulations
  • Steady State
  • Unmanned Aerial Vehicles
  • Unmanned Vehicles
  • Vehicle Tracks

Fields of Study

  • Computer science

Readers

  • Robotics and Automation.