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Multi-UAV formation control via deep reinforcement learning and multi-step experience storage in dense obstacle environments

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Transactions of the Institute of Measurement and Control

Published online on

Abstract

Transactions of the Institute of Measurement and Control, Ahead of Print.
This paper presents a deep reinforcement learning (DRL)-based Multi-Agent Control for Formation and Obstacle Avoidance (MACFOA) algorithm to solve collaborative formation and obstacle avoidance decision-making for unmanned aerial vehicle (UAV) systems in ...