参与全球首个VLA+RL框架的开发！清华大学团队成员招募了～

Core Viewpoint - The article introduces RLinf as the world's first RL infrastructure designed for training embodied large models, emphasizing its focus on VLA+RL tasks in the embodied domain and future feature expansions [1]. Group 1: Project Overview - RLinf is positioned as a pioneering platform for embodied large model training, with a unique emphasis on VLA+RL tasks [1]. - The project website is available for further information and resources [2]. Group 2: Technical Features - RLinf supports various simulators and real-world robotics applications, including ManiSkill, Franka Arm, and RoboTwin, among others [4]. - The platform incorporates multiple models such as VLA, OpenVLA, and GROOT, alongside a range of algorithms including PPO, SAC, and LoRA SFT [4]. Group 3: Recruitment Opportunities - The project is actively recruiting for master's, doctoral, postdoctoral, and research assistant positions, with opportunities linked to prominent institutions like Tsinghua University [5]. - There are pathways for non-academic participants to be recommended for leadership roles in various companies, offering competitive salaries and cutting-edge research directions [6]. Group 4: Contact Information - Interested parties can reach out to the RLinf project lead, Yu Chao, via email for further inquiries [7].