Multi-Vehicle Cooperative Search with Uncertain Prior Information

Abstract

We present a possible solution for the multi-vehicle cooperative search problem via the surrogate optimization method. We establish a discrete mathematical model for the multi-vehicle cooperative search stationary target with uncertain prior information. We reformulate the Past, Present and Predicted Future (PPP) algorithm we introduced in previous work based on the new model and propose an implementation to adapt to the new scenario. Monte Carlo simulations indicate that the new implementation achieves better performance. Moreover, the scalability of the PPP algorithm is addressed.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 2004
Accession Number
ADA421407

Entities

People

  • Chunlei Zhang
  • Corey Schumacher
  • Raul Ordonez

Organizations

  • University of Dayton

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Aircrafts
  • Algorithms
  • Autonomous Navigation
  • Communication Channels
  • Computational Science
  • Coordinate Systems
  • Equations
  • Guidance
  • Mathematical Models
  • Military Research
  • Models
  • Monte Carlo Method
  • Optimization
  • Scalability
  • Simulations

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Robotics and Automation.