群体行为
固定翼
计算机科学
对抗制
控制器(灌溉)
控制理论(社会学)
水准点(测量)
点(几何)
粒子群优化
遥控水下航行器
数学优化
最优化问题
控制(管理)
工程类
算法
移动机器人
机器人
人工智能
数学
翼
航空航天工程
大地测量学
生物
地理
几何学
农学
作者
Joonwon Choi,Min-Guk Seo,Hyo‐Sang Shin,Hyondong Oh
标识
DOI:10.1109/taes.2022.3169127
摘要
This paper proposes a coverage-based adversarial swarm defence algorithm. The defender swarm composed of fixed-wing unmanned aerial vehicles (UAVs) is assumed to have explosives onboard to intercept an adversarial swarm. The proposed approach consists of two steps: i) impact point optimization and ii) model predictive control (MPC)-based impact time control. The impact point optimization periodically optimizes impact points for the corresponding UAVs to maximize the coverage within the hostile swarm while minimizing the common impact time. The optimization domain is limited to a physically reachable area of UAVs with the common impact time. Besides, the MPC-based impact time controller is designed to ensure the multiple UAVs to arrive the generated time-varying impact points simultaneously. Numerical simulations are performed to prove the feasibility and efficiency of the proposed swarm defence algorithm.
科研通智能强力驱动
Strongly Powered by AbleSci AI