Underwater acoustic sensor networks (UASNs) have attracted considerable attention and
are extensively employed for tracking underwater targets. However, due to the complex …

Due to the unknown motion model and the complexity of the environment, the problem of
target tracking for autonomous underwater vehicles (AUVs) became one of the major …

Considering the complexities of the modern maritime operational environment and aiming
for effective safe navigation and communication maintenance, research into the …

With the rapid development of underwater communication, sensing, automation, robot
technologies, autonomous underwater vehicle (AUV) swarms are gradually becoming …

In recent years, deep reinforcement learning (DRL) has developed rapidly and has been
applied to multi-UAV target tracking (MTT) research. However, DRL still faces challenges in …

This paper studies a guidance and control framework of multiple autonomous surface
underwater vehicles (multi-ASUV) based on deep reinforcement learning (DRL) for target …

Non-cooperative target tracking technology has significant applications in the field of ocean,
serving both military and civilian purposes. The emerging underwater acoustic sensor …

Communication is the cornerstone of UAV swarms to transmit information and achieve
cooperation. However, artificially designed communication protocols usually rely on prior …

With the advantages of easy deployment and flexible usage, unmanned aerial vehicle (UAV)
has advanced the multitarget tracking (MTT) applications. The UAV-MTT system has great …

This paper combines deep reinforcement learning (DRL) with meta-learning and proposes a
novel approach, named meta twin delayed deep deterministic policy gradient (Meta-TD3), to …