Distributed Hybrid Information and Plan Consensus HIPC for Semi-autonomous UAV Teams

Abstract

The research objective of this project was to increase the capabilities of decentralized task allocation algorithms. Progress has been made on several different fronts, including: a) chance-constrained task allocation, b) task allocation with tasks defined as Markov Decision Processes, c) guaranteeing network connectivity during mission execution, d) allowing the use of non-submodular score functions during the decentralized allocation, and e) decreasing the convergence time by utilizing all of the information available in the network, f) hardware results that demonstrate the difficulty of planning in communication contested environments and the utility of using LICA algorithms, and g) a tutorial on the basics of decentralized task allocation for a general audience is currently in revision for Control Systems Magazine. Combining these results has significantly improved the state of the art capabilities of decentralized task allocation and work continues to refine these approaches.

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Document Details

Document Type
Technical Report
Publication Date
Sep 18, 2015
Accession Number
ADA627417

Entities

People

  • Jonathan How

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies
  • Human Systems
  • Space

DTIC Thesaurus Topics

  • Ad Hoc Networks
  • Air Force Research Laboratories
  • Algorithms
  • Communication Channels
  • Communication Networks
  • Computations
  • Consensus Algorithms
  • Control Systems
  • Convergence
  • Electronic Mail
  • Environment
  • Failure Mode And Effect Analysis
  • Geometry
  • Mesh Networks
  • Military Research
  • Situational Awareness
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Instructional Design and Training Evaluation.
  • Joint Military Operations and Doctrine.
  • Operations Research