P-RAG: Progressive Retrieval Augmented Generation For Planning on Embodied Everyday Task
University of Science and Technology of China（中国科学技术大学）；Institute of Artificial Intelligence, Hefei Comprehensive National Science Center（合肥综合性国家科学中心人工智能研究院）
Embodied Everyday Task is a popular task in the embodied AI community, requiring agents to make a sequence of actions based on natural language instructions and visual observations. Traditional learning-based approaches face two challenges. Firstly, natural language instructions often lack explicit task planning. Secondly, extensive training is required to equip models with knowledge of the task environment. Previous works based on Large Language Model (LLM) either suffer from poor performance due to the lack of task-specific knowledge or rely on ground truth as few-shot samples. To address the above limitations, we propose a novel approach called Progressive Retrieval Augmented Generation (P-RAG), which not only effectively leverages the powerful language processing capabilities of LLMs but also progressively accumulates task-specific knowledge without ground-truth. Compared to the conventional RAG methods, which retrieve relevant information from the database in a one-shot manner to assist generation, P-RAG introduces an iterative approach to progressively update the database. In each iteration, P-RAG retrieves the latest database and obtains historical information from the previous interaction as experiential references for the current interaction. Moreover, we also introduce a more granular retrieval scheme that not only retrieves similar tasks but also incorporates retrieval of similar situations to provide more valuable reference experiences. Extensive experiments reveal that P-RAG achieves competitive results without utilizing ground truth and can even further improve performance through self-iterations.
BEHAVIOR-1K: A Human-Centered, Embodied AI Benchmark with 1,000 Everyday Activities and Realistic Simulation
Stanford University（斯坦福大学）；The University of Texas at Austin（德克萨斯大学奥斯汀分校）；The University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；University of Southern California（南加州大学）；Salesforce Research（Salesforce研究院）
Position: Robot Privacy as Embodied Boundary Work. Connecting Capabilities, Contexts, and Design Responses in Everyday Robotics
The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；Tsinghua University（清华大学）；Beijing Academy of Artificial Intelligence（北京智源人工智能研究院）；The Hong Kong University of Science and Technology（香港科技大学）
BioProVLA-Agent: An Affordable, Protocol-Driven, Vision-Enhanced VLA-Enabled Embodied Multi-Agent System with Closed-Loop-Capable Reasoning for Biological Laboratory Manipulation
Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education, East China University of Science and Technology, Shanghai, CN（能源化工过程智能制造教育部重点实验室，东华大学，上海，中国）；Department of Computer Science and Engineering, East China University of Science and Technology, Shanghai, CN（东华大学计算机科学与工程系，上海，中国）；Department of Laboratory Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, CN（复旦大学附属瑞金医院检验医学科，上海，中国）；School of Information Science and Technology, Shihezi University, Shihezi, CN（石河子大学信息科学与技术学院，石河子，中国）
LLM-Empowered Embodied Agent for Memory-Augmented Task Planning in Household Robotics
Automation and Control Institute, Faculty of Electrical Engineering, TU Wien（自动化与控制研究所，电气工程学院，维也纳技术大学）；AIT Austrian Institute of Technology GmbH, Center for Vision, Automation and Control（奥地利技术研究所（AIT）有限公司，视觉、自动化与控制中心）
D3D-GEN: Robot-Aware Domain-Grounded Interactive 3D World Generation for Social Robotics
Singapore Management University（新加坡管理大学）；Technical University Berlin（柏林工业大学）；Max Planck Institute（马克斯·普朗克研究所）；Technical University Braunschweig（布伦瑞克工业大学）
Operation Veja: Fixing Fundamental Concepts Missing from Modern Roleplaying Training Paradigms
Divergence 2% LLC；Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign（电气与计算机工程系伊利诺伊大学厄巴纳-香槟分校）；Department of Computer Science University of Illinois Urbana-Champaign（计算机科学系伊利诺伊大学厄巴纳-香槟分校）
From Language to Action: Can LLM-Based Agents Be Used for Embodied Robot Cognition?
Institute of AI and Autonomous Systems (A 2 S)（人工智能与自主系统研究所）；Hochschule Bonn-Rhein-Sieg（波恩-莱茵-锡格大学）；Division for Systems and Control（系统与控制系）；Chalmers University of Technology（查尔姆斯理工大学）；Fraunhofer Institute for Intelligent Analysis and Information Systems（弗劳恩霍夫智能分析与信息系统研究所）
