发表机构
Universidad Politécnica de Madrid; Centre for Automation and Robotics (CAR), Universidad Politécnica de Madrid (UPM-CSIC); University of Luxembourg（马德里理工大学; 马德里理工大学自动化与机器人中心（UPM-CSIC）; 卢森堡大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出一种二维分类法，区分互惠意识、共享态势感知和团队态势感知，并通过搜索救援案例阐明各自的协调要求，为多机器人集体意识的设计与比较奠定基础。
AI 中文摘要
随着机器人团队在动态和非结构化环境中处理日益复杂的任务，有效的协调要求智能体保持对环境、队友和任务状态的准确、一致的表征。我们认为，互惠意识、共享态势感知和团队态势感知——这三个在多机器人系统文献中被广泛引用的概念——并不是可以互换的：它们形成了一个包含层级，其中每种类型在范围上包含前一种，并且跨越了一个从完全个体化理解（MA）到完全统一理解（SSA）的分布谱系，而TSA则占据一个混合位置。我们通过一个二维分类法来确立这一点，该分类法沿着意识对象和意识分布两个轴组织。将这些术语视为同义词会模糊每个术语对机器人系统所施加的精确协调要求。一个异构空中和地面机器人的搜索与救援案例研究将每个分类法位置具体化为具体的协调要求。这些发现为多机器人系统中集体意识的规范化规范、设计和比较提供了概念基础。
英文摘要
As robotic teams tackle increasingly complex tasks in dynamic and unstructured environments, effective coordination requires agents to maintain accurate, aligned representations of their environment, teammates, and mission state. We argue that Mutual Awareness, Shared Situational Awareness, and Team Situational Awareness --- three concepts widely invoked in the multi-robot systems literature --- are not interchangeable: they form a containment hierarchy in which each type subsumes the previous in scope, and span a distribution spectrum from fully individualized understanding (MA) to fully uniform understanding (SSA), with TSA occupying a mixed position. We establish this through a two-dimensional taxonomy organized along the object of awareness and awareness distribution axes. Treating these terms as synonyms obscures the precise coordination requirements each imposes on a robotic system. A Search and Rescue case study with heterogeneous aerial and ground robots grounds each taxonomy position in concrete coordination requirements. These findings provide a conceptual foundation for principled specification, design, and comparison of collective awareness in multi-robot systems.
