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 language | English (US) |
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Article number | 91 |
Journal | Algorithms |
Volume | 14 |
Issue number | 3 |
DOIs | |
State | Published - 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