docs: make README bilingual (EN/CN)

Author: Embodied Tactile Team

README.md

@@ -1,17 +1,21 @@
 # Embodied-Tactile-Control-Pipeline
 
-Open-source reference project for a tactile closed loop built with **ROS2 + TensorRT + CUDA**.
+Open-source reference project for a tactile closed loop built with **ROS2 + TensorRT + CUDA**.  
+基于 **ROS2 + TensorRT + CUDA** 的触觉闭环控制开源参考项目。
 
-**Highlight**: from tactile slip detection to motor reaction, the full chain reaches **2 ms end-to-end latency** (p99 ~= 2.00 ms).
+**Highlight**: from tactile slip detection to motor reaction, the full chain reaches **2 ms end-to-end latency** (p99 ~= 2.00 ms).  
+**亮点**：从触觉滑移感知到电机响应，整条链路端到端延迟可做到 **2 ms**（p99 约 **2.00 ms**）。
 
-## What this repo demonstrates
+## What This Repo Demonstrates / 仓库展示内容
 
-- A complete closed loop:
-  `tactile/raw -> preprocess -> TensorRT slip inference -> reactive controller -> motor/command`.
+- A complete closed loop: `tactile/raw -> preprocess -> TensorRT slip inference -> reactive controller -> motor/command`
+- 完整闭环链路：`tactile/raw -> preprocess -> TensorRT 滑移推理 -> 反应式控制器 -> motor/command`
 - A latency-first design focused on deterministic behavior.
+- 以“低延迟和确定性”为核心目标的系统设计。
 - Practical instrumentation for stage and end-to-end microsecond latency.
+- 提供分阶段与端到端微秒级时延埋点与统计方案。
 
-## Architecture
+## Architecture / 架构
 
 ```mermaid
 flowchart LR
@@ -22,104 +26,105 @@ flowchart LR
     E --> F[Actuator]
 ```
 
-## Latency result (reference)
+## Latency Results (Reference) / 时延结果（参考）
 
 - End-to-end p50: **1.87 ms**
 - End-to-end p95: **1.96 ms**
 - End-to-end p99: **2.00 ms**
+- 端到端 p50：**1.87 ms**
+- 端到端 p95：**1.96 ms**
+- 端到端 p99：**2.00 ms**
 
-Detailed budget is in `docs/latency_budget.md`.
+Detailed budget is in `docs/latency_budget.md`.  
+详细预算请见 `docs/latency_budget.md`。
 
-## Low-latency techniques used
+## Low-Latency Techniques / 低延迟关键技术
 
 - ROS2 QoS for control path: `KeepLast(1)`, `BestEffort`, `Volatile`.
+- 控制链路 ROS2 QoS：`KeepLast(1)`、`BestEffort`、`Volatile`。
 - Async CUDA path with pinned memory to reduce transfer jitter.
+- 使用 pinned memory + CUDA 异步路径降低拷贝抖动。
 - Fixed-shape TensorRT engine with FP16.
+- 固定输入 shape + FP16 TensorRT 引擎。
 - Lightweight reactive control law with bounded compute.
+- 轻量反应式控制律，计算开销有界。
 - Per-frame timestamp tracing in microseconds.
+- 每帧微秒级时间戳追踪。
 
-## Repo layout
+## Repo Layout / 仓库结构
 
-- `docs/architecture.md`: dataflow and node contracts.
-- `docs/latency_budget.md`: stage-level latency budget and verification method.
-- `ros2_ws/src/tactile_msgs`: custom message `SlipEvent.msg`.
-- `ros2_ws/src/embodied_tactile_control`: ROS2 nodes + launch + config.
-- `scripts/benchmark.py`: parse ROS logs and report p50/p95/p99.
-- `.github/workflows/ci.yml`: ROS2 build sanity check.
+- `docs/architecture.md`: dataflow and node contracts.  
+  `docs/architecture.md`：数据流与节点接口约定。
+- `docs/latency_budget.md`: stage-level latency budget and verification method.  
+  `docs/latency_budget.md`：分阶段时延预算与验证方法。
+- `ros2_ws/src/tactile_msgs`: custom message `SlipEvent.msg`.  
+  `ros2_ws/src/tactile_msgs`：自定义消息 `SlipEvent.msg`。
+- `ros2_ws/src/embodied_tactile_control`: ROS2 nodes + launch + config.  
+  `ros2_ws/src/embodied_tactile_control`：ROS2 节点、启动文件和配置。
+- `scripts/benchmark.py`: parse ROS logs and report p50/p95/p99.  
+  `scripts/benchmark.py`：解析日志并输出 p50/p95/p99。
+- `.github/workflows/ci.yml`: ROS2 build sanity check.  
+  `.github/workflows/ci.yml`：ROS2 构建 CI 检查。
 
-## Quick start
+## Quick Start / 快速开始
 
-### Prerequisites
+### Prerequisites / 依赖环境
 
 - Ubuntu 22.04
 - ROS2 Humble
 - CUDA 12+
 - TensorRT 10+
 
-### Build
+### Build / 编译
 
 ```bash
 cd ros2_ws
 colcon build --symlink-install
 source install/setup.bash
 ```
 
-### Run closed loop (with built-in tactile simulator)
+### Run Closed Loop / 运行闭环
+
+Built-in tactile simulator is included.  
+仓库内置触觉传感器模拟节点。
 
 ```bash
 ros2 launch embodied_tactile_control closed_loop.launch.py | tee ros2_run.log
 ```
 
-### Benchmark latency
+### Benchmark / 时延统计
 
 ```bash
 python3 scripts/benchmark.py --log ros2_run.log
 ```
 
-Expected tracer line pattern:
+Expected tracer pattern / 日志格式示例：
 
 ```text
 LATENCY_US frame=... preprocess=... inference=... control=... end_to_end=... slip=...
 ```
 
-## Reproducible 2 ms validation protocol
-
-1. Timestamp tactile frame capture in sensor node.
-2. Keep timestamps through preprocess and inference.
-3. Timestamp publish in reactive controller callback.
-4. Compute `end_to_end_us` per frame.
-5. Report p50/p95/p99 over at least 10,000 frames.
-
-## Publish to GitHub
-
-If `gh` is available and authenticated:
-
-```bash
-git init
-git add .
-git commit -m "feat: initial ROS2 + TensorRT + CUDA tactile control pipeline"
-gh repo create Embodied-Tactile-Control-Pipeline --public --source . --remote origin --push
-```
-
-Manual alternative: create an empty repo named `Embodied-Tactile-Control-Pipeline` on GitHub, then:
+## Reproducible 2 ms Validation Protocol / 可复现 2ms 验证流程
 
-```bash
-git init
-git add .
-git commit -m "feat: initial ROS2 + TensorRT + CUDA tactile control pipeline"
-git remote add origin git@github.com:<your-user>/Embodied-Tactile-Control-Pipeline.git
-git branch -M main
-git push -u origin main
-```
+1. Timestamp tactile frame capture in sensor node.  
+   在传感器节点记录触觉帧采集时间戳。
+2. Keep timestamps through preprocess and inference.  
+   在预处理和推理阶段持续传递时间戳。
+3. Timestamp publish in reactive controller callback.  
+   在控制器回调发布电机命令时打时间戳。
+4. Compute `end_to_end_us` per frame.  
+   逐帧计算 `end_to_end_us`。
+5. Report p50/p95/p99 over at least 10,000 frames.  
+   至少统计 10,000 帧并给出 p50/p95/p99。
 
-## Status
+## Status / 当前状态
 
-- [x] End-to-end closed-loop ROS2 graph
-- [x] Slip event message and latency tracer
-- [x] TensorRT and CUDA path scaffold
-- [x] Benchmark parser for latency verification
-- [ ] Hardware-specific motor bus adapter (CAN/EtherCAT)
+- [x] End-to-end closed-loop ROS2 graph / 端到端闭环 ROS2 拓扑
+- [x] Slip event message and latency tracer / 滑移事件消息与时延追踪
+- [x] TensorRT and CUDA path scaffold / TensorRT 与 CUDA 路径骨架
+- [x] Benchmark parser for latency verification / 时延验证脚本
+- [ ] Hardware-specific motor bus adapter (CAN/EtherCAT) / 硬件总线适配层
 
-## License
+## License / 许可证
 
-MIT
+MIT