Joint Optimization of Control and Communication in Autonomous UAV Swarms: Challenges, Potentials, and Framework

作者：Changhua Yao, Hui Tian, Cong Wang, Liubin Song, Jun Jing, Wenfeng Ma · 发表于：IEEE Wireless Communications · 年份：2021 · DOI：10.1109/mwc.011.2100036 · 被引用次数：7 · 研究领域：UAV Applications and Optimization、Distributed Control Multi-Agent Systems、Reinforcement Learning in Robotics

The unmanned aerial vehicle (UAV) swarm has drawn much attention for its wide range of potential applications. However, most UAV swarms rely on manual remote control or preprogramming, leaving autonomous cooperation as a challenging issue. Control and communication are two important pillars intra-autonomous-swarm, and the competition for limited resources between control and communication needs to be coordinated effectively in a swarm. In this article, the challenges and potentials of autonomous UAV swarm control and communication are discussed first. Then a new perspective on joint optimization of the two issues is presented, aiming at the swarm's task handling capability. Furthermore, a task-oriented integration of communication and control (ToICC) framework is proposed, including a route of mathematization for the task handling capability and a game-based distributed multi-agent cooperative learning approach. Finally, some potential applications and an illustrative case are provided to demonstrate the usefulness and effectiveness of the proposed ToICC framework.