论文标题
VG-warm:一个基于视觉的基因调节网络,用于无人机群行为出现
VG-Swarm: A Vision-based Gene Regulation Network for UAVs Swarm Behavior Emergence
论文作者
论文摘要
无人驾驶飞机(UAV)动态包围是一个具有巨大潜力的新兴领域。研究人员通常会从生物系统中获得灵感,要么从宏观世界(如鱼类学校或鸟类羊群),也可以从类似于基因调节网络(GRN)的微世界中获得灵感。但是,大多数群体控制算法都依赖于集中式控制,全球信息获取以及相邻代理之间的通信。在这项工作中,我们提出了一种纯粹基于视觉和grn的分布式群体控制方法,而无需任何直接通信,例如,例如无人机可以生成一个陷入的模式,以纯粹基于其安装的全向视觉传感器包围无人机的逃避目标。还设计了描述每个无人机行为模型的有限状态计算机(FSM),以便一群无人机可以以集成的方式共同完成目标的搜索和捕获。我们在各种模拟和现实世界实验中验证了所提出方法的有效性和效率。
Unmanned Aerial Vehicles (UAVs) dynamic encirclement is an emerging field with great potential. Researchers often get inspiration from biological systems, either from macro-world like fish schools or bird flocks etc, or from micro-world like gene regulatory networks (GRN). However, most swarm control algorithms rely on centralized control, global information acquisition, and communications among neighboring agents. In this work, we propose a distributed swarm control method based purely on vision and GRN without any direct communications, in which swarm agents of e.g. UAVs can generate an entrapping pattern to encircle an escaping target of UAV based purely on their installed omnidirectional vision sensors. A finite-state-machine (FSM) describing the behavioral model of each drone is also designed so that a swarm of drones can accomplish searching and entrapping of the target collectively in an integrated way. We verify the effectiveness and efficiency of the proposed method in various simulation and real-world experiments.