Distributed UAV Swarm Formation Control via Object-Focused, Multi-Objective SARSA

2018 ◽  
Author(s):  
Christian Speck ◽  
Donald J. Bucci
Keyword(s):  
Formation Control ◽  
Multi Objective ◽  
Uav Swarm ◽  
Swarm Formation

Modeling and Simulation of UAV Swarm Formation Control in Response to Wind Gusts

2019 ◽  
Author(s):  
Daniel E. Findeis ◽  
Michael G. Balchanos ◽  
George Vachtsevanos ◽  
Dimitri N. Mavris
Keyword(s):  
Modeling And Simulation ◽  
Formation Control ◽  
Wind Gusts ◽  
Uav Swarm ◽  
Swarm Formation

scholarly journals UAV swarm formation control based on adaptive finite-time observer disturbance

2020 ◽  
Vol 50 (4) ◽  
pp. 423-438
Author(s):  
YueQian LIANG ◽  
Qi DONG ◽  
YanJie ZHAO
Keyword(s):  
Finite Time ◽  
Formation Control ◽  
Uav Swarm ◽  
Swarm Formation

scholarly journals UAV Formation Shape Control via Decentralized Markov Decision Processes

Algorithms ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 91
Author(s):  
Md Ali Azam ◽  
Hans D. Mittelmann ◽  
Shankarachary Ragi
Keyword(s):  
Control Problem ◽  
Shape Control ◽  
Formation Control ◽  
Three Dimensional ◽  
Geographical Region ◽  
Dynamic Programming Method ◽  
Theoretic Approach ◽  
Control Approach ◽  
Uav Swarm ◽  
Markov Decision

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.

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