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基于局部交互的三维多智能体觅食策略

Three-Dimensional Multi-Agent Foraging Strategy Based on Local Interaction.

作者信息

Kim Jonghoek

机构信息

System Engineering Department, Sejong University, Seoul 05006, Republic of Korea.

出版信息

Sensors (Basel). 2023 Sep 23;23(19):8050. doi: 10.3390/s23198050.

DOI:10.3390/s23198050
PMID:37836880
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10575063/
Abstract

This paper considers a multi-agent foraging problem, where multiple autonomous agents find resources (called pucks) in a bounded workspace and carry the found resources to a designated location, called the base. This article considers the case where autonomous agents move in unknown 3-D workspace with many obstacles. This article describes 3-D multi-agent foraging based on local interaction, which does not rely on global localization of an agent. This paper proposes a 3-D foraging strategy which has the following two steps. The first step is to detect all pucks inside the 3-D cluttered unknown workspace, such that every puck in the workspace is detected in a provably complete manner. The next step is to generate a path from the base to every puck, followed by collecting every puck to the base. Since an agent cannot use global localization, each agent depends on local interaction to bring every puck to the base. In this article, every agent on a path to a puck is used for guiding an agent to reach the puck and to bring the puck to the base. To the best of our knowledge, this article is novel in letting multiple agents perform foraging and puck carrying in 3-D cluttered unknown workspace, while not relying on global localization of an agent. In addition, the proposed search strategy is provably complete in detecting all pucks in the 3-D cluttered bounded workspace. MATLAB simulations demonstrate the outperformance of the proposed multi-agent foraging strategy in 3-D cluttered workspace.

摘要

本文考虑一个多智能体觅食问题，即多个自主智能体在一个有界工作空间中寻找资源（称为圆盘），并将找到的资源运送到一个指定位置，即基地。本文考虑自主智能体在存在许多障碍物的未知三维工作空间中移动的情况。本文描述了基于局部交互的三维多智能体觅食，该方法不依赖于智能体的全局定位。本文提出了一种三维觅食策略，该策略有以下两个步骤。第一步是在三维杂乱未知工作空间中检测所有圆盘，以便以可证明的完全方式检测工作空间中的每个圆盘。下一步是生成从基地到每个圆盘的路径，然后将每个圆盘收集到基地。由于智能体无法使用全局定位，每个智能体依靠局部交互将每个圆盘运送到基地。在本文中，每个前往圆盘的路径上的智能体都用于引导一个智能体到达圆盘并将圆盘运送到基地。据我们所知，本文的新颖之处在于让多个智能体在三维杂乱未知工作空间中执行觅食和搬运圆盘任务，同时不依赖于智能体的全局定位。此外，所提出的搜索策略在检测三维杂乱有界工作空间中的所有圆盘方面可证明是完全的。MATLAB仿真证明了所提出的多智能体觅食策略在三维杂乱工作空间中的优越性能。

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