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使用无人机和无人地面传感器进行协同监视与追踪。

Cooperative surveillance and pursuit using unmanned aerial vehicles and unattended ground sensors.

作者信息

Las Fargeas Jonathan, Kabamba Pierre, Girard Anouck

机构信息

Department of Aerospace Engineering, University of Michigan, Ann Arbor, MI 48105, USA.

出版信息

Sensors (Basel). 2015 Jan 13;15(1):1365-88. doi: 10.3390/s150101365.

Abstract

This paper considers the problem of path planning for a team of unmanned aerial vehicles performing surveillance near a friendly base. The unmanned aerial vehicles do not possess sensors with automated target recognition capability and, thus, rely on communicating with unattended ground sensors placed on roads to detect and image potential intruders. The problem is motivated by persistent intelligence, surveillance, reconnaissance and base defense missions. The problem is formulated and shown to be intractable. A heuristic algorithm to coordinate the unmanned aerial vehicles during surveillance and pursuit is presented. Revisit deadlines are used to schedule the vehicles' paths nominally. The algorithm uses detections from the sensors to predict intruders' locations and selects the vehicles' paths by minimizing a linear combination of missed deadlines and the probability of not intercepting intruders. An analysis of the algorithm's completeness and complexity is then provided. The effectiveness of the heuristic is illustrated through simulations in a variety of scenarios.

摘要

本文考虑了一组无人驾驶飞行器在友好基地附近执行监视任务时的路径规划问题。这些无人驾驶飞行器不具备具有自动目标识别能力的传感器,因此依靠与放置在道路上的无人地面传感器通信来检测潜在入侵者并对其成像。该问题是由持续情报、监视、侦察和基地防御任务所引发的。该问题被公式化并证明是难以处理的。提出了一种在监视和追踪过程中协调无人驾驶飞行器的启发式算法。使用重新访问期限来名义上安排飞行器的路径。该算法利用传感器的检测结果来预测入侵者的位置,并通过最小化错过期限和未拦截入侵者概率的线性组合来选择飞行器的路径。然后对该算法的完备性和复杂性进行了分析。通过在各种场景下的仿真说明了该启发式算法的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b55e/4327082/235a9ea70d1d/sensors-15-01365f1.jpg

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