Interception of automated adversarial drone swarms in partially observed environments

IF 5.8 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Integrated Computer-Aided Engineering Pub Date : 2021-04-06 DOI:10.3233/ICA-210653
Daniel Saranovic, M. Pavlovski, W. Power, Ivan Stojkovic, Z. Obradovic
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引用次数: 5

Abstract

As the prevalence of drones increases, understanding and preparing for possible adversarial uses of drones and drone swarms is of paramount importance. Correspondingly, developing defensive mechanisms in which swarms can be used to protect against adversarial Unmanned Aerial Vehicles (UAVs) is a problem that requires further attention. Prior work on intercepting UAVs relies mostly on utilizing additional sensors or uses the Hamilton-Jacobi-Bellman equation, for which strong conditions need to be met to guarantee the existence of a saddle-point solution. To that end, this work proposes a novel interception method that utilizes the swarm’s onboard PID controllers for setting the drones’ states during interception. The drone’s states are constrained only by their physical limitations, and only partial feedback of the adversarial drone’s positions is assumed. The new framework is evaluated in a virtual environment under different environmental and model settings, using random simulations of more than 165,000 swarm flights. For certain environmental settings, our results indicate that the interception performance of larger swarms under partial observation is comparable to that of a one-drone swarm under full observation of the adversarial drone.
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在部分可观察的环境中拦截自动对抗无人机群
随着无人机的普及,了解和准备无人机和无人机群可能的对抗用途是至关重要的。相应地,开发防御机制,使蜂群可以用来防御敌对的无人机(uav)是一个需要进一步关注的问题。先前拦截无人机的工作主要依赖于利用附加传感器或使用Hamilton-Jacobi-Bellman方程,该方程需要满足强条件以保证鞍点解的存在。为此,本工作提出了一种新的拦截方法,该方法利用蜂群的机载PID控制器在拦截期间设置无人机的状态。无人机的状态仅受其物理限制的约束,并且仅假设对抗性无人机位置的部分反馈。新框架在不同环境和模型设置下的虚拟环境中进行评估,使用超过16.5万次蜂群飞行的随机模拟。对于特定的环境设置,我们的研究结果表明,在部分观察下,较大的蜂群的拦截性能与在敌对无人机完全观察下的单无人机蜂群的拦截性能相当。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Integrated Computer-Aided Engineering
Integrated Computer-Aided Engineering 工程技术-工程:综合
CiteScore
9.90
自引率
21.50%
发文量
21
审稿时长
>12 weeks
期刊介绍: Integrated Computer-Aided Engineering (ICAE) was founded in 1993. "Based on the premise that interdisciplinary thinking and synergistic collaboration of disciplines can solve complex problems, open new frontiers, and lead to true innovations and breakthroughs, the cornerstone of industrial competitiveness and advancement of the society" as noted in the inaugural issue of the journal. The focus of ICAE is the integration of leading edge and emerging computer and information technologies for innovative solution of engineering problems. The journal fosters interdisciplinary research and presents a unique forum for innovative computer-aided engineering. It also publishes novel industrial applications of CAE, thus helping to bring new computational paradigms from research labs and classrooms to reality. Areas covered by the journal include (but are not limited to) artificial intelligence, advanced signal processing, biologically inspired computing, cognitive modeling, concurrent engineering, database management, distributed computing, evolutionary computing, fuzzy logic, genetic algorithms, geometric modeling, intelligent and adaptive systems, internet-based technologies, knowledge discovery and engineering, machine learning, mechatronics, mobile computing, multimedia technologies, networking, neural network computing, object-oriented systems, optimization and search, parallel processing, robotics virtual reality, and visualization techniques.
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