Abstract:
Multi-drone systems have been widely used for
various applications which will otherwise be difficult to be done
us ing only single drone operation. One important challenge in
such multi-drone system operation is how to optimize their
performance when required to operate in unknown environment.
In this paper, a multi-agent reinforcement learning (MARL)
scheme is proposed to initiate a cooperative operation of a multidrone
system that is tasked to perform a 3D space mapping or
a region. The proposed MARL method is designed to optimize
the multi-drone system's energy consumption by introducing a
sparse cooperative interaction scheme. In this regard, each drone
either communicates with the other when needed or perform its
individual learning otherwise. Simulation results are shown to
illustrate the convergence/optimality of the used MARL scheme.
Description:
Makalah dipresentasikan pada 2023 International Conference on Computer, Cont rol, Informatics and its Applications (IC31NA). 04 - 05 Oktober 2023. p.1-6