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Coalition Formation for Multiple Heterogeneous UAVs Cooperative Search and Prosecute with Communication Constraints

机译:多种异构无人机合作搜索和起诉的联盟形成与通信约束

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To improve the cooperative search and attack effectiveness of multiple heterogeneous unmanned aerial vehicles (UAVs) in unknown environment, a novel coalition formation method with communication constraints is presented in this paper. First, the coalition formation model is established on the basis of minimizing the target attack delay and minimizing the coalition size with the constraint of required resources and simultaneous strike. Second, considering communication constrains such as limited communication ranges and communication delays, a mechanism was developed in order to find the potential coalition members within a maximum number of hops over a dynamic UAV network. Third, to reduce the huge computational complexity in coalition formation optimization solution we propose a Multistage Sub-Optimal Coalition Formation Algorithm (MSOCFA) with low computational complexity. Furthermore, in order to enable multiple cooperative UAVs accomplish the search and prosecute missions autonomously, a distributed autonomous control strategy is proposed which is based on the Finite-State Machine (FSM). Comparison simulations are carried out to demonstrate that how the potential coalition members finding technique impact on the coalition achieved by MSOCFA. The effects of number of maximum allowed hops for a message and hop delay are studied by employing Monte-Carlo method. The experimental reveals that, in the cases of large communication delay, forming a coalition from the immediate neighbors is sufficient for a good performance in term of the mission completion time. Under smaller delays, including neighbors up to a few hops will increase performance, and any additional increase in hop count will degrade performance.
机译:为了改善在未知环境多个异构无人驾驶飞行器(UAV)的协同搜索和攻击效力,具有通信约束的新型联合形成方法本文提出。首先,联盟形成模型尽量减少目标攻击延迟和减少与所需的资源和同时打击的约束联盟尺寸的基础上建立的。其次,考虑到通信约束,例如有限的通信范围和通信延迟,一个机制,以便找到跳的最大数量之内的潜在联盟成员在一个动态的无人机网络发达。第三,减少联盟形成优化解决方案的巨大计算复杂性,我们建议以低计算复杂度的多级次优联盟形成算法(MSOCFA)。此外,为了使多个合作无人机完成搜索和起诉任务自主,分布式自主控制策略,提出了一种基于有限状态机(FSM)。比较仿真进行证明的潜在联盟成员的联盟查找技术的影响如何通过MSOCFA实现。通过采用蒙特卡罗法进行了研究用于消息和跳延迟最大允许跳数的影响。实验表明,在大的通信延迟的情况下,形成从近邻的联盟足够用于的任务完成时间期限有不错的表现。在较小的延迟,包括邻居高达几跳会提高性能,并在跳数的任何额外的增加会降低性能。

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