基于分布式反集群算法的无人水面艇区域覆盖方法
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摘要
海上无人系统覆盖问题可广泛应用于搜索营救、区域侦察观测、信息采集等任务,针对无人水面艇对海面区域进行区域覆盖的问题,采用模仿独居动物社会行为的分布式反集群算法,使得无人水面艇系统能够通过自组织行为实现良好的动态覆盖性能,因此使其具有更高的可扩展性及环境适应性。首先建立个体的包含覆盖历史的信息图,其次进行反集群算法的避障、去中心化及自私这3个基本属性的数学公式描述,然后计算每个个体在每一时刻的最大化收益方向,使得每个个体能够最大化累计覆盖面积及最小化个体之间的重叠覆盖部分。仿真结果表明,基于覆盖历史及个体局部通信交互,能够实现避障功能,并且可以达到100%的覆盖率,同时可尽量减少重叠覆盖。
Unmanned system area coverage on sea surface has been widely used in the tasks of search and rescue, regional reconnaissance and observation, information acquisition, etc. In this paper, the distributed antiflocking algorithm inspired by the solitary behavior of some animals who try to separate from their species in most of daily activities in order to maximize their own gains, is used to solve the problem of area coverage using unmanned surface vehicles(USVs) on sea surface. Antiflocking control algorithm enables a group of USVs to self-organize in an environment and provides impressive dynamic coverage performances. Therefore, such system exhibits better scalability and adaptability to environmental changes.Firstly, a simplified version of distributed information maps including sensing history is constructed. Then mathematical interpretations to the heuristic rules including selfishness, decentering and collision avoidance are introduced. Finally, the positions of selfishness goals should be selected in such a way that they would maximize the cumulative area coverage and minimize the overlap of each other's sensing coverage. Simulation results show that based on sensing history and local interaction, this paper can achieve the collision avoidance capability and achieve 100% area coverage, while overlapping coverage can be minimized.
Unmanned system area coverage on sea surface has been widely used in the tasks of search and rescue, regional reconnaissance and observation, information acquisition, etc. In this paper, the distributed antiflocking algorithm inspired by the solitary behavior of some animals who try to separate from their species in most of daily activities in order to maximize their own gains, is used to solve the problem of area coverage using unmanned surface vehicles(USVs) on sea surface. Antiflocking control algorithm enables a group of USVs to self-organize in an environment and provides impressive dynamic coverage performances. Therefore, such system exhibits better scalability and adaptability to environmental changes.Firstly, a simplified version of distributed information maps including sensing history is constructed. Then mathematical interpretations to the heuristic rules including selfishness, decentering and collision avoidance are introduced. Finally, the positions of selfishness goals should be selected in such a way that they would maximize the cumulative area coverage and minimize the overlap of each other's sensing coverage. Simulation results show that based on sensing history and local interaction, this paper can achieve the collision avoidance capability and achieve 100% area coverage, while overlapping coverage can be minimized.
引文
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[2]吴青坡,周绍磊,闫实.复杂区域多UAV覆盖侦察方法研究[J].战术导弹技术,2016(1):50-55+63.WU Qing-po, ZHOU Shao-lei, YAN Shi. Multi-UAVs cooperative coverage reconnaissance in complex area[J].Tactical Missile Technology, 2016(1):50-55+63.
[3] Teraoka S, Ushio T, Kanazawa T. Voronoi coveragecontrol with time-driven communication for mobile sensing networks with obstacles[C]. 50~(th)IEEE Conference on Decision and Control and European Control Conference,2011:1980-1985.
[4] Mansouri S S, Kanellakis C, Georgoulas G, et al. 2D visual area coverage and path planning coupled with camera footprints[J]. Control Engineering Practice, 2018, 75:1-16.
[5] Gage D W. Randomized search strategies with imperfect sensors[C]. Proceedings of SPIE Mobile RobotsⅧ,1994, 2058:270-279.
[6] Miao Y Q, Khamis A, Kamel M S. Applying antiflocking model in mobile surveillance systems[C]. 1~(st)IEEE International Conference on Autonomous and Intelligent Systems, 2010:1-6.
[7] Ganganath N, Cheng C T, Tse C K. Distributed antiflocking algorithms for dynamic coverage of mobile sensor networks[J]. IEEE Transactions on Industrial Informatics,2016, 12(5):1795-1805.
[8] Su H S, Wang X F, Lin Z L. Flocking of multi-agents with a virtual leader[J]. IEEE Transactions on Automatic Control, 2009, 54(2):293-307.
[9] Liu B Y, Dousse O, Nain P, et al. Dynamic coverage of mobile sensor networks[J]. IEEE Transactions on Parallel&Distributed Systems, 2013, 24(2):301-311.