Graph soft actor–critic reinforcement learning for large-scale distributed multirobot coordination
Learning distributed cooperative policies for large-scale multirobot systems remains a
challenging task in the multiagent reinforcement learning (MARL) context. In this work, we …
challenging task in the multiagent reinforcement learning (MARL) context. In this work, we …
Reinforcement learning-based formation pinning and shape transformation for swarms
Z Dong, Q Wu, L Chen - Drones, 2023 - mdpi.com
Swarm models hold significant importance as they provide the collective behavior of self-
organized systems. Boids model is a fundamental framework for studying emergent …
organized systems. Boids model is a fundamental framework for studying emergent …
Reinforcement learning for joint detection and mapping using dynamic UAV networks
Dynamic radar networks (DRNs), usually composed of flying unmanned aerial vehicles
(UAVs), have recently attracted great interest for time-critical applications, such as search …
(UAVs), have recently attracted great interest for time-critical applications, such as search …
Safe multi-agent reinforcement learning for formation control without individual reference targets
In recent years, formation control of unmanned vehicles has received considerable interest,
driven by the progress in autonomous systems and the imperative for multiple vehicles to …
driven by the progress in autonomous systems and the imperative for multiple vehicles to …
Time-aware MADDPG with LSTM for multi-agent obstacle avoidance: a comparative study
Intelligent agents and multi-agent systems are increasingly used in complex scenarios, such
as controlling groups of drones and non-player characters in video games. In these …
as controlling groups of drones and non-player characters in video games. In these …
Flexible formation control using hausdorff distance: A multi-agent reinforcement learning approach
While fixed topology formation control with a cen-tralized controller has been studied for
multi-agent systems, it remains challenging to develop robust distributed control policies that …
multi-agent systems, it remains challenging to develop robust distributed control policies that …
Practical time‐varying formation cooperative control for high‐order nonlinear multi‐agent systems avoiding spatial resource conflict via safety constraints
X Ma, T Chou - International Journal of Robust and Nonlinear …, 2024 - Wiley Online Library
The operation of multi‐agent systems (MAS) in space necessitates considerations for
obstacle avoidance, collision prevention, and connectivity among agents. This coupling …
obstacle avoidance, collision prevention, and connectivity among agents. This coupling …
End-to-end decentralized formation control using a graph neural network-based learning method
Multi-robot cooperative control has been extensively studied using model-based distributed
control methods. However, such control methods rely on sensing and perception modules in …
control methods. However, such control methods rely on sensing and perception modules in …
HMA-SAR: Multi-Agent Search and Rescue for Unknown Located Dynamic Targets in Completely Unknown Environments
X Cao, M Li, Y Tao, P Lu - IEEE Robotics and Automation …, 2024 - ieeexplore.ieee.org
Multi-Agent Search and Rescue (MASAR) tasks, challenged by unknown environments and
the unpredictable movements of unknown dynamic targets, suffer from inefficiencies in …
the unpredictable movements of unknown dynamic targets, suffer from inefficiencies in …
Distributed Policy Gradient for Linear Quadratic Networked Control with Limited Communication Range
This paper proposes a scalable distributed policy gradient method and proves its
convergence to near-optimal solution in multi-agent linear quadratic networked systems …
convergence to near-optimal solution in multi-agent linear quadratic networked systems …