Core Insights - The article focuses on the development and sharing of datasets related to embodied intelligence and robotics, highlighting various projects and their significance in advancing robotic manipulation and learning capabilities [3][4][5][10]. Group 1: Datasets and Projects - BRMData is introduced as a dataset aimed at empowering embodied manipulation for household tasks, with a project link provided for further exploration [4]. - AgiBot World Colosseo is presented as a large-scale manipulation platform designed for scalable and intelligent embodied systems, with a project link included [4]. - RoboMIND serves as a benchmark for multi-embodiment intelligence normative data for robot manipulation, with a project link for access [4]. - OpenX-Embodiment focuses on robotic learning datasets and RT-X models, with a project link available [4]. - DROID is highlighted as a large-scale in-the-wild robot manipulation dataset, with a project link provided [5]. - RH20T is described as a comprehensive robotic dataset for learning diverse skills in one-shot, with a project link included [5]. - BridgeDataV2 is mentioned as a dataset for robot learning at scale, with a project link for further details [5]. - RT-2 emphasizes vision-language foundation models as effective robot imitators, with a project link available [5]. - RT-1 is introduced as a robotics transformer for real-world control at scale, with a project link provided [6]. - Bridge Data aims to boost the generalization of robotic skills with cross-domain datasets, with a project link included [7]. - BC-Z focuses on zero-shot task generalization with robotic imitation learning, with a project link available [7]. Group 2: Community and Collaboration - The article promotes the "Embodied Intelligence Heart" knowledge community as the first developer community in China focused on embodied intelligence, emphasizing its role as a professional exchange platform [10]. - The community covers various topics including datasets, simulation platforms, large models, reinforcement learning, and robotic manipulation, with a summary of over 30 learning paths and 60 datasets available [10]. - The community encourages collaboration among nearly 200 companies and institutions, fostering academic and industrial exchanges [10][13].