基于广义Voronoi划分的异构传感器多智能体搜索
Generalized Voronoi Partition Based Multi-Agent Search using Heterogeneous Sensors
摘要：
在本文中，我们提出了异构多智能体系统的搜索策略。多个代理，配备了通信小工具，计算能力，和具有异构能力的传感器，部署在搜索空间中收集信息，如目标的存在。缺乏信息的搜索空间被建模为一个不确定性密度分布。减少了搜索代理收集信息的不确定性。我们提出了一个广义的Voronoi分区将异质性的传感器的能力，并设计多个代理的最佳部署策略，最大限度地提高一个单一的步骤搜索效率。最优部署形成了两种搜索策略的基础，即{ \em异构顺序部署和搜索}和{ \em异构组合部署和搜索}。我们证明了所提出的策略可以降低不确定性密度到任意低的水平，在理想的条件下。我们提供了一些正式的分析结果有关的稳定性和收敛性的建议的控制律，空间分布的策略下的限制，如限制代理的最大速度，代理移动速度恒定和传感器范围的限制。仿真结果验证了本文所提出的理论结果。
英文摘要：
In this paper we propose search strategies for heterogeneous multi-agent systems. Multiple agents, equipped with communication gadget, computational capability, and sensors having heterogeneous capabilities, are deployed in the search space to gather information such as presence of targets. Lack of information about the search space is modeled as an uncertainty density distribution. The uncertainty is reduced on collection of information by the search agents. We propose a generalization of Voronoi partition incorporating the heterogeneity in sensor capabilities, and design optimal deployment strategies for multiple agents, maximizing a single step search effectiveness. The optimal deployment forms the basis for two search strategies, namely, {\em heterogeneous sequential deploy and search} and {\em heterogeneous combined deploy and search}. We prove that the proposed strategies can reduce the uncertainty density to arbitrarily low level under ideal conditions. We provide a few formal analysis results related to stability and convergence of the proposed control laws, and to spatial distributedness of the strategies under constraints such as limit on maximum speed of agents, agents moving with constant speed and limit on sensor range. Simulation results are provided to validate the theoretical results presented in the paper.
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