Uav formation shape control via decentralized markov decision processes

Md Ali Azam, Hans D. Mittelmann, Shankarachary Ragi

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we present a decentralized unmanned aerial vehicle (UAV) swarm formation control approach based on a decision theoretic approach. Specifically, we pose the UAV swarm motion control problem as a decentralized Markov decision process (Dec-MDP). Here, the goal is to drive the UAV swarm from an initial geographical region to another geographical region where the swarm must form a three-dimensional shape (e.g., surface of a sphere). As most decision-theoretic formulations suffer from the curse of dimensionality, we adapt an existing fast approximate dynamic programming method called nominal belief-state optimization (NBO) to approximately solve the formation control problem. We perform numerical studies in MATLAB to validate the performance of the above control algorithms.

Original languageEnglish (US)
Article number91
JournalAlgorithms
Volume14
Issue number3
DOIs
StatePublished - Mar 2021

Keywords

  • Approximate dynamic programming
  • Decentralized Markov decision process
  • Formation control
  • Swarm intelligence

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Numerical Analysis
  • Computational Theory and Mathematics
  • Computational Mathematics

Fingerprint

Dive into the research topics of 'Uav formation shape control via decentralized markov decision processes'. Together they form a unique fingerprint.

Cite this