Local information-based control for probabilistic swarm distribution guidance
Local information-based control for probabilistic swarm distribution guidance
复制标题
基于本地信息的概率群体分布引导控制
作者：
Inmo Jang;Hyo;A. Tsourdos
本文提出了一种用于群体分布制导的闭环分散框架，该框架利用当前群体状态的反馈增益，将均匀的智能体分散在仓上以获得期望的密度分布。与现有工作的关键区别在于，所提出的框架只利用局部信息而不是全局信息来产生随机策略的反馈增益。对本地信息的依赖带来了各种优势，包括减少代理之间的通信、更短的获取新信息的时间范围、异步实施以及无需先验任务知识的可部署性。我们的理论分析表明，即使只利用局部信息，所提出的框架也保证了代理收敛到期望的状态，同时保持了现有闭环系统的优点。此外，分析还明确了实现所提议框架的所有优点的设计要求。我们提供了实现实例，并报告了经验测试的结果。测试结果验证了该框架的有效性，并验证了该框架在通信网络部分断开的情况下的健壮性增强。
This paper proposes a closed-loop decentralised framework for swarm distribution guidance, which disperses homogeneous agents over bins to achieve a desired density distribution by using feedback gains from the current swarm status. The key difference from existing works is that the proposed framework utilises only local information, not global information, to generate the feedback gains for stochastic policies. Dependency on local information entails various advantages including reduced inter-agent communication, a shorter timescale for obtaining new information, asynchronous implementation, and deployability without a priori mission knowledge. Our theoretical analysis shows that, even utilising only local information, the proposed framework guarantees convergence of the agents to the desired status, while maintaining the advantages of existing closed-loop approaches. Also, the analysis explicitly provides the design requirements to achieve all the advantages of the proposed framework. We provide implementation examples and report the results of empirical tests. The test results confirm the effectiveness of the proposed framework and also validate the robustness enhancement in a scenario of partial disconnection of the communication network.
影响因子：
3.3
作者：
Arvin, Farshad;Espinosa, Jose;Lennox, Barry
通讯作者：
Lennox, Barry