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

This paper is concerned with the problem of multi-UAV roundup inspired by hierarchical
cognition consistency learning based on an interaction mechanism. First, a dynamic …

In this paper, a finite-time convergent continuous action iterated dilemma (CAID) with
topological optimization is proposed to overcome the limitations of traditional methods …

Unmanned Aerial Vehicle (UAV) swarm offers extended coverage and is a vital solution for
many applications. A key issue in UAV swarm control is to cover all targets while maintaining …

Generally, the coverage control is studied in a convex region, in which the agent kinematics
and the coverage environment both have strong limitations. It is difficult to directly apply …

Reinforcement learning (RL) is an unsupervised machine learning that does not requires
pre-assigned labeled data to learn. It is implemented in many areas such as robotics …

Achieving a connected, collision-free and time-efficient coverage in unknown environments
is challenging for multi-agent systems. Particularly, agents with second-order dynamics are …

This work addresses the problem of motion planning for a group of nonholonomic robots
under Visible Light Communication (VLC) connectivity requirements. In particular, we …

In public safety networks (PSNs), it is an important issue how reliable data transmission
recovers when some base stations (BSs) are damaged by natural disasters. An unmanned …

The multi-radar ship platform is equipped with various types of radars and many other
electronic sensors, which leads to a great risk of electromagnetic conflicts during the working …