This paper introduces CognitiveOS, a disruptive system based on multiple transformer-based models, endowing robots of various types with cognitive abilities not only for communication with humans but also for task resolution through physical interaction with the environment. The system operates smoothly on different robotic platforms without extra tuning. It autonomously makes decisions for task execution by analyzing the environment and using information from its long-term memory. The system underwent testing on various platforms, including quadruped robots and manipulator robots, showcasing its capability to formulate behavioral plans even for robots whose behavioral examples were absent in the training dataset. Experimental results revealed the system's high performance in advanced task comprehension and adaptability, emphasizing its potential for real-world applications. The chapters of this paper describe the key components of the system and the dataset structure. The dataset for fine-tuning step generation model is provided at the following link: link coming soon

翻译：本文介绍CognitiveOS——一个基于多个Transformer架构模型的颠覆性系统，能为各类机器人赋予认知能力，不仅实现与人类交流，还能通过物理环境交互完成复杂任务。该系统无需额外调参即可在异构机器人平台上稳定运行，通过分析环境并调用长期记忆信息自主制定任务执行决策。该系统在四足机器人、机械臂等多种平台上完成测试，展现出对训练数据集中未出现行为范例的机器人也能生成行为规划的能力。实验结果表明，该系统在高级任务理解与适应性方面表现卓越，凸显出真实场景应用潜力。本文各章节详细阐述了系统关键组件与数据集结构，其中用于微调步骤生成模型的数据集可通过以下链接获取（待公布）。