70 lines
1.6 KiB
Markdown
70 lines
1.6 KiB
Markdown
# V1 标准中间数据格式
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第一版流水线**不直接读** dlog / rscap。请先把数据整理成下列格式。
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## IMU
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文件:`imu.csv` 或 `imu.npz`
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### CSV
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```text
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t,gx,gy,gz,ax,ay,az
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0.000000000,0.01,-0.02,0.00,0.05,-0.03,9.81
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...
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```
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| 列 | 含义 | 单位 |
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|---|---|---|
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| t | IMU 时钟时间 | s |
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| gx,gy,gz | 角速度 | rad/s |
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| ax,ay,az | 比力/加速度 | m/s² |
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### NPZ
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数组:`t (N,)`, `gyro (N,3)`, `acc (N,3)`,含义同上。
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> IMU 与 LiDAR 的时间原点可以不同。流水线会估计常值偏置:`t_imu = t_lidar + delta_t`。
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## LiDAR
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目录结构:
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```text
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lidar_session/
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├── frames_index.csv
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└── frames/
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├── frame_00000.npz
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├── frame_00001.npz
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└── ...
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```
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### frames_index.csv
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```text
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frame_id,filename,t_start,t_end
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0,frames/frame_00000.npz,10.000,10.100
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1,frames/frame_00001.npz,10.100,10.200
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```
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也兼容旧列名 `file`(NumPy 读取时可能变成 `file_`)。
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### 每帧 NPZ
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- `points`: `float64/float32`,形状 `(N, 3)`,LiDAR 直角坐标系,单位米
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## 时间不同步能不能用?
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可以,前提是:
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1. 两边都覆盖同一段**有角速度激励**的物理运动(尤其是转弯);
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2. 偏置近似为**常数**(短会话);
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3. `--time-offset-search-s` 足够覆盖可能的偏移(默认 ±1 s,可加大)。
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若两段数据完全不是同一趟行驶,或只有静止 IMU、没有重叠运动,则无法估 δt,标定会被 `blocked`。
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## 最小可用会话
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- IMU:建议含静止段 + 运动段,采样率稳定
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- LiDAR:建议 ≥ 20 帧,场景有墙/柱等结构,含转弯
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