物理人工智能基础
Fundamentals of Physical AI
AI总结：
本研究阐述物理人工智能（Physical AI）的六大基础原理（具身性、感知、行动等），构建其理论框架，揭示智能为身体-环境-经验交互的涌现现象，为物理智能系统的设计与评估提供概念基础。
摘要：
本研究将从科学和系统的视角阐述物理人工智能（Physical AI）的基本原理，旨在构建一个连贯的理论框架，描述智能系统的物理具身性、感官感知、行动能力、学习过程及情境敏感性。经典人工智能方法依赖符号处理和数据驱动模型，而Physical AI将智能视为身体、环境与经验间真实交互的涌现现象。本文提出的六大基础为具身性、感官感知、运动行动、学习、自主性和情境敏感性，构成设计与评估物理智能系统的概念基础。理论上，这六大原理并非松散的功能模块，而是形成能量、信息、控制与情境持续交互的闭环控制回路，使系统从物理经验而非数据库中生成意义，实现将智能视为物理具身过程的范式转变。Physical AI将学习理解为智能体与环境间结构耦合的变化，并通过康复诊所自适应辅助机器人的实际场景阐释理论模型，表明物理智能源于即时具身经验而非抽象计算，展示六大基础在真实系统中的交互机制。
英文摘要：
This work will elaborate the fundamental principles of physical artificial intelligence (Physical AI) from a scientific and systemic perspective. The aim is to create a theoretical foundation that describes the physical embodiment, sensory perception, ability to act, learning processes, and context sensitivity of intelligent systems within a coherent framework. While classical AI approaches rely on symbolic processing and data driven models, Physical AI understands intelligence as an emergent phenomenon of real interaction between body, environment, and experience. The six fundamentals presented here are embodiment, sensory perception, motor action, learning, autonomy, and context sensitivity, and form the conceptual basis for designing and evaluating physically intelligent systems. Theoretically, it is shown that these six principles do not represent loose functional modules but rather act as a closed control loop in which energy, information, control, and context are in constant interaction. This circular interaction enables a system to generate meaning not from databases, but from physical experience, a paradigm shift that understands intelligence as an physical embodied process. Physical AI understands learning not as parameter adjustment, but as a change in the structural coupling between agents and the environment. To illustrate this, the theoretical model is explained using a practical scenario: An adaptive assistant robot supports patients in a rehabilitation clinic. This example illustrates that physical intelligence does not arise from abstract calculation, but from immediate, embodied experience. It shows how the six fundamentals interact in a real system: embodiment as a prerequisite, perception as input, movement as expression, learning as adaptation, autonomy as regulation, and context as orientation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
