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---
title: "Real-World RL真机强化学习"
created: 2026-06-29
updated: 2026-06-29
type: concept
tags: [reinforcement-learning, robotics, safety, embodied-intelligence]
sources: [[real-world-safe-exploration-see-2026]]
confidence: high
---
# Real-World RL真机强化学习
> [[reinforcement-learning|强化学习]] 在**物理世界真实环境**中的直接训练范式。与仿真训练的本质区别:**没有"重来"按钮**,每次交互都可能有真实代价。
## 与仿真训练的对立
| 维度 | 仿真训练 | 真机 RL |
|------|---------|---------|
| 试错成本 | 近乎零 | 机器损坏 / 人员伤亡 |
| 数据效率 | 可无限采样 | 每次交互昂贵 |
| 安全机制 | 可选 | **绝对必需** |
| 动力学精度 | 受仿真器 fidelity 限制 | 天然精确 |
## 核心挑战
[[safe-exploration|安全探索]] 是真机 RL 的首要难题——不仅最终策略要安全,**整个训练过程的每一刻都不能违反安全约束**。
## 两种训练模式
- **OTOI**Offline Training, Online Implementation仿真训练 → 线上部署,无需安全探索
- **SOTI**Simultaneous Online Training and Implementation边训练边部署**必须安全探索**
大多数真实机器人/自动驾驶场景只能走 SOTI 路线。
## 相关概念
- [[safe-exploration|安全探索]]
- [[safe-equilibrium-exploration|SEE 论文]]
- [[feasible-zone|可行域]]
- [[reinforcement-learning|强化学习]]