Open Access
Hybrid Formation Control for Multi-Robot Hunters Based on Multi-Agent Deep Deterministic Policy Gradient
Publication type: Journal Article
Publication date: 2021-12-21
scimago Q3
SJR: 0.335
CiteScore: 3.0
Impact factor: —
ISSN: 18033814, 25713701
Computational Mathematics
Theoretical Computer Science
General Computer Science
Abstract
The cooperation between mobile robots is one of the most important topics of interest to researchers, especially in the many areas in which it can be applied. Hunting a moving target with random behavior is an application that requires robust cooperation between several robots in the multi-robot system. This paper proposed a hybrid formation control for hunting a dynamic target which is based on wolves’ hunting behavior in order to search and capture the prey quickly and avoid its escape and Multi Agent Deep Deterministic Policy Gradient (MADDPG) to plan an optimal accessible path to the desired position. The validity and the effectiveness of the proposed formation control are demonstrated with simulation results.
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Hamlich M., Hamed O. Hybrid Formation Control for Multi-Robot Hunters Based on Multi-Agent Deep Deterministic Policy Gradient // Mendel. 2021. Vol. 27. No. 2. pp. 23-29.
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Hamlich M., Hamed O. Hybrid Formation Control for Multi-Robot Hunters Based on Multi-Agent Deep Deterministic Policy Gradient // Mendel. 2021. Vol. 27. No. 2. pp. 23-29.
Cite this
RIS
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TY - JOUR
DO - 10.13164/mendel.2021.2.023
UR - https://doi.org/10.13164/mendel.2021.2.023
TI - Hybrid Formation Control for Multi-Robot Hunters Based on Multi-Agent Deep Deterministic Policy Gradient
T2 - Mendel
AU - Hamlich, M
AU - Hamed, O
PY - 2021
DA - 2021/12/21
PB - Brno University of Technology
SP - 23-29
IS - 2
VL - 27
SN - 1803-3814
SN - 2571-3701
ER -
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BibTex (up to 50 authors)
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@article{2021_Hamlich,
author = {M Hamlich and O Hamed},
title = {Hybrid Formation Control for Multi-Robot Hunters Based on Multi-Agent Deep Deterministic Policy Gradient},
journal = {Mendel},
year = {2021},
volume = {27},
publisher = {Brno University of Technology},
month = {dec},
url = {https://doi.org/10.13164/mendel.2021.2.023},
number = {2},
pages = {23--29},
doi = {10.13164/mendel.2021.2.023}
}
Cite this
MLA
Copy
Hamlich, M., and O Hamed. “Hybrid Formation Control for Multi-Robot Hunters Based on Multi-Agent Deep Deterministic Policy Gradient.” Mendel, vol. 27, no. 2, Dec. 2021, pp. 23-29. https://doi.org/10.13164/mendel.2021.2.023.