基于群的分布式目标包围算法及其在精准农业监测任务中的应用

G. D. Carolis, Ryan K. Williams, A. Gasparri
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引用次数: 2

摘要

本文提出了一种基于群体的方法,用于在三维环境中协调多智能体系统(MAS)围绕目标进行精确农业监测任务。具体来说,我们的动机是围绕大型树冠的目标,以便协同收集有关树木健康状况的信息。这一目标是通过改进经典的基于势的群体设计来实现的,该设计采用了一种新颖的拓扑切换策略,允许期望的包围行为出现。由此产生的交互协议要求智能体仅利用局部信息,确保无碰撞轨迹,而无需对编码网络拓扑的无向时变图进行限制性假设。数值结果验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Swarm-Based Distributed Algorithm for Target Encirclement with Application to Monitoring Tasks in Precision Agriculture Scenarios
This paper proposes a swarm-based approach for coordinating a multi-agent system (MAS) in a 3D environment to encircle a target for monitoring tasks in precision agriculture. Specifically, we are motivated by the objective of encircling large tree canopies in order to collaboratively gather information on tree health status. This goal is achieved by enhancing classical potential-based swarm design with a novel topology switching policy allowing the desired encirclement behavior to emerge. The resulting interaction protocol requires agents to utilize only local information, ensuring collision-free trajectories without restrictive assumptions on the undirected time-varying graph encoding the network topology. Numerical results are presented to demonstrate the effectiveness of the proposed approach.
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