针对多机器人追捕死角问题的自适应编队算法
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摘要
多机器人刚性编队无法灵活调整队形,易出现追捕死角现象,导致追捕者无法准确高效地完成追捕。为此,提出一种自适应刚性结构编队算法。构造编队中心控制器使编队中心无限趋近目标,设计队形控制器随目标所处位置动态调整队形。在此基础上,追捕者根据目标所在位置和环境条件,结合改进的刚性结构法自适应地选择合适队形,从而完成围捕。仿真结果表明,相对刚性编队算法,该算法的追捕时间和能耗比均较低,且能够避免追捕死角现象产生。
Rigid formation of multi-robot can not flexibly adjust formation,leading to the phenomenon of chasing blind angle easily,so that the pursuers can not accurately and efficiently complete the chase. To solve this problem,an adaptive rigid structural formation algorithm is proposed. The formation center controller makes the formation center infinitely close to the target. The formation controller is designed to dynamically adjust the formation according to the location of the target. On this basis,the tracker,in accordance with the position of the target and the environmental conditions,combined with the improved rigid structure method to choose the appropriate formation adaptively,so as to complete hunting. Simulation results show that,the tracking time and energy consumption ratio of the algorithm are lower than that of the rigid formation algorithm,and the hunting blind angle can be avoided.
Rigid formation of multi-robot can not flexibly adjust formation,leading to the phenomenon of chasing blind angle easily,so that the pursuers can not accurately and efficiently complete the chase. To solve this problem,an adaptive rigid structural formation algorithm is proposed. The formation center controller makes the formation center infinitely close to the target. The formation controller is designed to dynamically adjust the formation according to the location of the target. On this basis,the tracker,in accordance with the position of the target and the environmental conditions,combined with the improved rigid structure method to choose the appropriate formation adaptively,so as to complete hunting. Simulation results show that,the tracking time and energy consumption ratio of the algorithm are lower than that of the rigid formation algorithm,and the hunting blind angle can be avoided.
引文
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[2]YUAN M,ZHAOLI Y E,CHENG S,et al.Multi-robot cooperative handling based on immune network algorithm regulated by interferon[EB/OL].[2017-06-20].http://en.cnki.com.cn/Article_en/CJFDTotal-ZNXT2014 01014.htm.
[3]周浦城,洪炳镕,蔡则苏.多机器人运动目标搜索策略研究[J].哈尔滨工业大学学报,2005,37(7):879-882.
[4]CHEN F,REN W,CAO Y.Surrounding control in cooperative agent networks[J].Systemsand Control Letters,2010,59(11):704-712.
[5]唐朝君.多智能体系统一致性问题与包含控制问题研究[D].成都:电子科技大学,2012.
[6]段敏.多智能体系统分布式包围控制[D].重庆:重庆大学,2015.
[7]方宝富,潘启树,洪炳镕,等.多追捕者-单一逃跑者追逃问题实现成功捕获的约束条件[J].机器人,2012,34(3):282-291.
[8]FARINELLI A,IOCCHI L,NARDI D.Distributed on-line dynamic task assignment for multi-robot patrolling[J].Autonomous Robots,2016,41(6):1-25.
[9]张旭,贾磊磊,陈群.关于多机器人围捕协调路径策略研究[J].计算机仿真,2016(6):357-361.
[10]HE W,CHEN Y,YIN Z.Adaptive neural network control of an uncertain robot with full-state constraints[J].IEEE Transactions on Cybernetics,2016,46(3):620-629.
[11]谢德胜,徐友春,万剑,等.基于RTK-GPS的轮式移动机器人轨迹跟随控制[J].机器人,2017,39(2):221-229.
[12]夏瑜,吴小俊,李菊,等.基于改进融合策略的多特征跟踪算法[J].机器人,2016,38(4):428-436.
[13]王勋,张纪阳,张代兵,等.无人机编队飞行快速试验系统设计[J].机器人,2017,39(2):160-166,175.
[14]LEE S K,FEKETE S P,MCLURKIN J.Structured triangulation in multi-robot systems:coverage,patrolling,voronoi partitions,and geodesic centers[J].International Journal of Robotics Research,2016,35(10):312-334.
[15]ZELAZO D,FRANCHI A,ALLGWER F,et al.Rigidity maintenance control for multi-robot systems[EB/OL].[2017-06-20].http://www.roboticsproceedings.org/rss08/p60.pdf.
[16]MENG D,JIA Y,DU J,et al.On iterative learning algorithms for the formation control of nonlinear multiagent systems[J].Automatica,2014,50(1):291-295.
[17]GIL S,KUMAR S,KATABI D,et al.Adaptive communication in multi-robot systems using directionality of signal strength[J].International Journal of Robotics Research,2015,34(7):946-968.
[18]MATHEWS N,VALENTINI G,CHRISTENSEN A L,et al.Spatially targeted communication in decentralized multirobot systems[J].Autonomous Robots,2015,38(4):439-457.
[19]DICKERSON M.Multi-agent simulation,netlogo,and the recruitment of computer science majors[J].Journal of Computing Sciences in Colleges,2014,30:131-139.
[20]张国良,杜柏阳,孙一杰,等.基于预测控制的时滞多机器人编队脉冲控制[J].控制与决策,2016,31(8):1453-1460.
[21]黄海,张强,张树迪,等.欠驱动AUV自适应编队控制策略[J].哈尔滨工程大学学报,2015(5):633-637.
[22]徐志强,陈雪波.包含原理的群体机器人队形一致协调控制[J].智能系统学报,2015,10(2):301-306.
[23]王祥科,李迅,郑志强.多智能体系统编队控制相关问题研究综述[J].控制与决策,2013,28(11):1601-1613.
[24]WANG Q,ZHU Y,LI J,et al.Globally stable rigid formation control for multi-robot systems[C]//Proceedings of the 34th Chinese Control Conference.Washington D.C.,USA:IEEE Press,2015:7505-7510.
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