多智能体系统中基于局部测量信息的目标定位

Multi-agent target localization based on sampled local relative measurement under switching topology

针对多智能体系统中的定位问题,设计一种在变拓扑网络条件下的分布式目标定位算法,使所有智能体实现目标的相对定位.假设智能体只能获取局部的测量信息并进行局部信息交换.算法包括成对智能体之间相互定位算法和基于一致性的目标定位融合算法,对算法的成立条件和收敛误差进行分析,并通过仿真实验验证所提出算法的有效性.

In this paper, a distributed localization algorithm is designed to copes with the multi-agent target localization problem under switching topology, which can estimate the relative position of the silent target in each agent＇s local frame.Agents can only detect local measurements and exchange local information. The whole algorithm includes two parts： the algorithm for relative localization between pairwise agents, and the consensus-like fusion target localization algorithm based on the pairwise localization algorithm. The rigorous analysis for the topology condition and convergence of estimate error is presented. Simulation with and without measurement noises are also carried out to verify the effectiveness of the proposed algorithms.