With growth in the use of autonomous Unmanned Ground Vehicle (UGV) for automated data collection from construction projects, the problem of inter-disciplinary semantic data sharing and exchanges between construction and robotic domains has attracted construction stakeholders' attention. Cross-domain data translation requires detailed specifications especially when it comes to semantic data translation. Building Information Modeling (BIM) and Geographic Information System (GIS) are the two technologies to capture and store construction data for indoor structure and outdoor environment respectively. In the absence of a standard format for data exchanges between the construction and robotic domains, the tools of both industries are yet to be integrated in a coherent deployment infrastructure. Hence, the semantics of BIM-GIS cannot be automatically integrated by any robotic platform. To enable semantic data transfer across domains, semantic web technology has been widely used in multidisciplinary areas for interoperability. We exploit it to pave the way to a smarter, quicker and more precise robot navigation on job-sites. This paper develops a semantic web ontology integrating robot navigation and data collection to convey the meanings from BIM-GIS to the robot. The proposed Building Information Robotic System (BIRS) provides construction data that are semantically transferred to the robotic platform and can be used by the robot navigation software stack on construction sites. To reach this objective, we first need to bridge the knowledge representation between construction and robotic domains. Then, we develop a semantic database to integrate with Robot Operating System (ROS) which can communicate with the robot and the navigation system in order to provide the robot with semantic building data at each step of data collection. Finally, the proposed system is validated through a case study.
Instance-Level Semantic Maps for Vision Language Navigation
KCIS, International Institute of Information Technology, Hyderabad（印度海得拉巴国际信息技术学院KCIS）；CSAIL, MIT（麻省理工学院计算机科学与人工智能实验室）；Hasan Kalyoncu University（哈桑·卡尔永朱大学）
Learning Traversability for Long Horizon Off-Road Navigation
J. Mike Walker ’66 Department of Mechanical Engineering, Texas A&M University（德克萨斯农工大学J. Mike Walker '66机械工程系）；DEVCOM Army Research laboratory（陆军研究实验室）
STONE Dataset: A Scalable Multi-Modal Surround-View 3D Traversability Dataset for Off-Road Robot Navigation
Interdisciplinary Program in Artificial Intelligence, Seoul National University（人工智能交叉学科项目，首尔国立大学）；Department of Electrical and Computer Engineering, Seoul National University（电气与计算机工程系，首尔国立大学）
Logic-Guided Socially-aware Robot Navigation World Model
School of Applied and Creative Computing, Purdue University（应用与创意计算学院，普渡大学）；Department of Computer Science, Purdue University（计算机科学系，普渡大学）；Department of Applied Artificial Intelligence, Sungkyunkwan University（应用人工智能系，成均馆大学）；Department of Computer Science and Department of Intelligent Systems Engineering, Indiana University Bloomington（计算机科学系和智能系统工程系，印第安纳大学布卢明顿分校）
Robust Localization, Mapping, and Navigation for Quadruped Robots
École Centrale de Nantes（法国南特中央理工大学）；Technical University of Darmstadt（德累斯顿技术大学）；Poznan University of Technology（波兹南理工大学）；IDEAS NCBR；German Research Center for AI (DFKI)（德国人工智能研究中心）；Università degli Studi di Milano（米兰大学）
ReaDy-Go: Real-to-Sim Dynamic 3D Gaussian Splatting Simulation for Environment-Specific Visual Navigation with Moving Obstacles
Department of Aerospace Engineering, Seoul National University（首尔国立大学航空航天工程系）；InnoCORE AI-Transformed Aerospace Research Center, KAIST（韩国科学技术院（KAIST）人工智能赋能航空航天研究中心）
MOANA: Multi-Radar Dataset for Maritime Odometry and Autonomous Navigation Application
Institute of Advanced Machines and Design, SNU, Seoul, S. Korea（先进机械与设计研究所，首尔国立大学）；Dept. of Mechanical Engineering, SNU, Seoul, S. Korea（机械工程系，首尔国立大学）；Seadronix, Seoul, S. Korea（Seadronix公司）；Defence Science and Technology Agency, Singapore（新加坡国防科学与技术局）
Enhancing Vision-Language Navigation with Multimodal Event Knowledge from Real-World Indoor Tour Videos
The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；Tsinghua University（清华大学）；Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI)（马尔代夫 bin Zayed 大学人工智能学院）；Hangzhou City University（杭州城市学院）
Bi3: A Biplatform, Bicultural, Biperson Dataset for Social Robot Navigation
Department of Robotics, University of Michigan（机器人系，密歇根大学）；LAAS-CNRS, University of Toulouse（LAAS-CNRS，图卢兹大学）；INRIA, University of Lorraine（INRIA，洛林大学）
Getting Robots Unfrozen and Unlost in Dense Pedestrian Crowds
Baidu Research（百度研究院）；City University of Hong Kong（香港城市大学）；Metoak Technology (Beijing) CO., LTD.（北京梅托克科技有限公司）；Fuzhou University（福州大学）；University of Maryland, College Park（马里兰大学帕克分校）
S2P2: Self-Supervised Goal-Directed Path Planning Using RGB-D Data for Robotic Wheelchairs
The Hong Kong University of Science and Technology（香港科技大学）；The Hong Kong Polytechnic University（香港理工大学）；the University of California San Diego（加州大学圣迭戈分校）
