Awareness and self-awareness are two different notions related to knowing the environment and itself. In a general context, the mechanism of self-awareness belongs to a class of co-called "self-issues" (self-* or self-star): self-adaptation, self-repairing, self-replication, self-development or self-recovery. The self-* issues are connected in many ways to adaptability and evolvability, to the emergence of behavior and to the controllability of long-term developmental processes. Self-* are either natural properties of several systems, such as self-assembling of molecular networks, or may emerge as a result of homeostatic regulation. Different computational processes, leading to a global optimization, increasing scalability and reliability of collective systems, create such a homeostatic regulation. Moreover, conditions of ecological survival, imposed on such systems, lead to a discrimination between "self" and "non-self" as well as to the emergence of different self-phenomena. There are many profound challenges, such as understanding these mechanisms, or long-term predictability, which have a considerable impact on research in the area of artificial intelligence and intelligent systems.
Universidad Politécnica de Madrid（马德里理工大学）；Centre for Automation and Robotics (CAR), Universidad Politécnica de Madrid (UPM-CSIC)（马德里理工大学自动化与机器人中心（UPM-CSIC））；University of Luxembourg（卢森堡大学）
University of Stuttgart（斯图加特大学）；Fraunhofer Institute for Biomedical Engineering（弗劳恩霍夫生物医学工程研究所）；UWE Bristol（西英格兰大学布里斯托尔分校）；Sheffield Hallam University（谢菲尔德哈勒姆大学）；Ubisense AG（Ubisense股份公司）；IMA, s.r.o.（IMA有限责任公司）
Heterogeneity for Increasing Performance and Reliability of Self-Reconfigurable Multi-Robot Organisms
University of Stuttgart（斯图加特大学）；Fraunhofer Institute for Biomedical Engineering (IBMT)（弗劳恩霍夫生物医学工程研究所（IBMT））；The BioRobotics Institute, Scuola Superiore Sant’Anna（圣安娜高等研究院生物机器人研究所）；Karlsruhe Institute of Technology (KIT)（卡尔斯鲁厄理工学院（KIT））；University of Tuebingen（图宾根大学）
Distributed Algorithm with Emergent Area Partitioning and Base Station's Situation Awareness for Multi-Robot Patrolling
Department of Mechanical Engineering, Materials Science, and Ocean Engineering, Graduate School of Engineering Science, Yokohama National University（机械工程、材料科学与海洋工程系，工程科学研究生院， Yokohama国立大学）；Faculty of Environment and Information Sciences, Yokohama National University（环境与信息科学系，Yokohama国立大学）
Decentralised construction of a global coordinate system in a large swarm of minimalistic robots
Tomas Bata University in Zlín（兹林托马斯巴塔大学）；New Jersey Institute of Technology（新泽西理工学院）；Université Libre de Bruxelles（布鲁塞尔自由大学）；University of Sheffield（谢菲尔德大学）
Safe Planner: Empowering Safety Awareness in Large Pre-Trained Models for Robot Task Planning
Harbin Institute of Technology（哈尔滨工业大学）；Intelligent Science & Technology Academy Limited of CASIC（中国航天科工集团智能科技研究院有限公司）；Institute of Computer Application Technology, Norinco Group（中国兵器工业集团计算机应用技术研究所）
An Exploratory Study on Human-Robot Interaction using Semantics-based Situational Awareness
Extreme Robotics Lab (ERL) and National Center for Nuclear Robotics (NCNR), University of Birmingham, UK（极端机器人实验室（ERL）和核机器人国家中心（NCNR）、英国伯明翰大学）；School of Electronic Engineering and Computer Science, Queen Mary University of London, UK（电子工程与计算机科学学院，伦敦女王玛丽大学）
Alternative Interfaces for Human-initiated Natural Language Communication and Robot-initiated Haptic Feedback: Towards Better Situational Awareness in Human-Robot Collaboration
Computational Design and Fabrication of Modular Robots with Untethered Control
Institute of Science and Technology Austria（奥地利科学与技术研究所）；University of Tsukuba（茨口大学）；Cluster Metaverse Lab（元宇宙集群实验室）；ETH Zurich（苏黎世联邦理工学院）；California Institute of Technology（加州理工学院）；The University of Osaka（大阪大学）
A Framework for Semantics-based Situational Awareness during Mobile Robot Deployments
University of Birmingham（伯明翰大学）；Birmingham Centre for Nuclear Education & Research (BCNER)（伯明翰核教育研究中心）；University of West Attica（西阿提卡大学）；Queen Mary University of London（伦敦大学玛丽皇后学院）
First Responders' Perceptions of Semantic Information for Situational Awareness in Robot-Assisted Emergency Response
Extreme Robotics Lab (ERL) and National Center for Nuclear Robotics (NCNR), University of Birmingham, UK（极端机器人实验室（ERL）和核机器人国家中心（NCNR）、伯明翰大学）；Department of Computer Science, Bioengineering, Robotics and Systems Engineering, University of Genova, Italy（计算机科学、生物工程、机器人学和系统工程系、热那亚大学）；School of Engineering Mathematics and Technology, University of Bristol, UK（工程数学与技术学院、布里斯托尔大学）；School of Electronic Engineering and Computer Science, Queen Mary University of London, UK（电子工程与计算机科学学院、伦敦女王大学）
If They Disagree, Will You Conform? Exploring the Role of Robots' Value Awareness in a Decision-Making Task
CONTACT Unit, Italian Institute of Technology, Genoa, Italy（意大利理工学院CONTACT单元，热那亚，意大利）；IDLab-AIRO, Ghent University – imec, Belgium（根特大学imec IDLab-AIRO，比利时）
Learning from Demonstration with Failure Awareness for Safe Robot Navigation
Department of Mechanical Engineering, The Hong Kong Polytechnic University（香港理工大学机械工程系）；College of Information Science and Technology, Eastern Institute of Technology（东华理工大学信息科学学院）；School of Computer Science and Technology, University of Science and Technology of China（中国科学技术大学计算机科学与技术学院）；Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University（香港理工大学航空与航空工程系）
在协作机器人的背景下，分布式态势感知对于支持机器人和人类代理团队中的集体智能至关重要，它可以用于个人和集体决策支持。这在与紧急救援和危机管理有关的应用中尤其重要。在操作任务期间，数据和知识由异构机器人和人类以不同的方式逐步收集。我们将其描述为\emph{Hastily Formed Knowledge Networks}（HFKNs）的创建。本文的重点是一个通用的分布式系统架构，支持创建HFKNs的机器人和人类的团队的规范和原型。收集的信息范围从低级传感器数据到高级语义知识，后者部分表示为RDF图。该框架包括一个同步协议和相关的算法，允许代理之间的数据和知识的自动分配和共享。这是通过代理之间共享的RDF图的分布式同步来完成的。SPARQL中指定的高级语义查询可以被机器人和人类用来从团队成员那里获取知识和数据内容。该系统的经验验证和所提出的算法的复杂性结果。此外，现场机器人的案例研究进行了描述，在一个合作的紧急救援情况下，同时使用完整的HFKN框架，使用几个无人机执行3D映射任务。
