智元发布SOP框架，让机器人在真实场景干活更稳定、更高效

Core Insights - The article discusses the advancements in embodied intelligence and humanoid robots, particularly focusing on the introduction of the SOP (Scalable Online Post-training) system, which aims to enhance the deployment of robots in real-world scenarios [1][3]. Group 1: SOP Framework - SOP is a universal robot framework that allows for the integration of various post-training algorithms, providing a foundational system for real-world applications [1][3]. - The framework is considered a critical step for robots to operate effectively in real-world environments, emphasizing the need for stability and reliability while maintaining generalization capabilities [3]. Group 2: Performance and Validation - The SOP framework was tested in a real environment where models operated continuously for 36 hours, performing repetitive tasks such as folding clothes [6]. - The integration of SOP with the HG-Dagger method resulted in a 33% overall performance improvement in complex tasks within retail environments, such as restocking and assembling boxes [6]. Group 3: Application Scenarios - Different application scenarios present varying degrees of implementation difficulty, with industrial manufacturing requiring high success rates and robustness, while home services and retail environments are more open but have less stringent performance requirements [7]. - The most commercially viable scenarios for immediate implementation are identified as industrial manufacturing and certain commercial service contexts, with broader deployment expected in supermarkets and home settings by 2026 [7].