多智能体切换控制实现声源定位，支持单目标追踪与多目标独立搜寻。
Multi Agent Switching Mode Controller for Sound Source localization
- 设计多智能体切换控制策略，根据场景自动切换追踪模式。
- 单源时保持刚性队形逼近目标，多源时各智能体独立搜索。
- 适用于无视线条件下的声源定位，适合机器人协同导航场景。
声源搜寻是机器人研究中的重要课题，尤其在依赖声学传感器的场景中，可在无法建立直接视线的情况下仍能定位目标。本文设计了一种基于声学的多智能体切换模式控制策略。考虑两种情形：单源定位中，智能体保持刚性编队向目标移动；多源场景中，各智能体独立搜寻目标。该方法提升了复杂环境下的定位鲁棒性与协作效率。
原文摘要 · Abstract (English)
Source seeking is an important topic in robotic research, especially considering sound-based sensors since they allow the agents to locate a target even in critical conditions where it is not possible to establish a direct line of sight. In this work, we design a multi- agent switching mode control strategy for acoustic-based target localization. Two scenarios are considered: single source localization, in which the agents are driven maintaining a rigid formation towards the target, and multi-source scenario, in which each agent searches for the targets independently from the others.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。