File size: 11,676 Bytes
8aa2acf | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 | # 仿真评测结果总汇 (GR00T N1.7 / Genie-Envisioner)
生成时间:2026-05-25 19:20:58 UTC
本文件汇总全部实验:① GR00T pair-grid 硬/软口径 ② GR00T all_factor full-factor ③ conflict 双轴 env success(GR00T vs Genie)④ VLM(Gemini-2.5-flash)FDR 对照。
数值为成功率 %;pair-grid/all_factor 均为 3-seed 平均。
---
# 一、GR00T pair-grid(硬口径,3-seed)
## color_size (HARD)
| ckpt | s42 | s40 | s41 | 3-seed 均 |
|---|---|---|---|---|
| color_size_Lrandom_f12 | 24.1 | 27.3 | 24.5 | **25.3%** |
| color_size_Lrandom_f18 | 35.6 | 34.7 | 34.3 | **34.8%** |
| color_size_Lrandom_f6 | 7.9 | 10.2 | 6.9 | **8.3%** |
| color_size_random_f12 | 13.4 | 15.3 | 11.6 | **13.4%** |
| color_size_random_f18 | 27.3 | 32.9 | 28.2 | **29.4%** |
| color_size_random_f6 | 9.7 | 9.3 | 10.6 | **9.8%** |
| color_size_stair_f12 | 28.2 | 28.2 | 28.2 | **28.2%** |
| color_size_stair_f18 | 26.9 | 27.8 | 25.9 | **26.8%** |
| color_size_stair_f6 | 7.4 | 8.3 | 6.0 | **7.2%** |
## color_size (EASY)
| ckpt | s42 | s40 | s41 | 3-seed 均 |
|---|---|---|---|---|
| color_size_Lrandom_f12 | 23.6 | 24.5 | 22.7 | **23.6%** |
| color_size_Lrandom_f18 | 36.6 | 38.0 | 37.0 | **37.2%** |
| color_size_Lrandom_f6 | 5.1 | 10.6 | 9.3 | **8.3%** |
| color_size_random_f12 | 14.4 | 14.8 | 16.2 | **15.1%** |
| color_size_random_f18 | 28.7 | 33.3 | 31.0 | **31.0%** |
| color_size_random_f6 | 6.9 | 11.1 | 6.9 | **8.3%** |
| color_size_stair_f12 | 29.2 | 27.8 | 29.6 | **28.8%** |
| color_size_stair_f18 | 26.4 | 25.5 | 27.8 | **26.5%** |
| color_size_stair_f6 | 9.3 | 8.3 | 6.5 | **8.0%** |
## color_spatial
| ckpt | s42 | s40 | s41 | 3-seed 均 |
|---|---|---|---|---|
| color_spatial_Lrandom_f18 | 52.4 | 42.9 | 46.7 | **47.3%** |
| color_spatial_random_f12 | 33.3 | 27.6 | 33.8 | **31.5%** |
| color_spatial_random_f18 | 42.4 | 36.7 | 41.0 | **40.0%** |
| color_spatial_random_f6 | 23.3 | 26.2 | 24.8 | **24.7%** |
| color_spatial_stair_f18 | 54.8 | 45.7 | 52.9 | **51.1%** |
| color_spatial_stair_f6 | 24.3 | 19.5 | 21.4 | **21.7%** |
## verb_spatial
| ckpt | s42 | s40 | s41 | 3-seed 均 |
|---|---|---|---|---|
| verb_spatial_Lrandom_f12 | 31.9 | 29.5 | 32.4 | **31.2%** |
| verb_spatial_Lrandom_f18 | 32.9 | 30.0 | 34.8 | **32.5%** |
| verb_spatial_Lrandom_f6 | 22.4 | 31.0 | 27.1 | **26.8%** |
| verb_spatial_random_f12 | 31.4 | 31.9 | 37.6 | **33.6%** |
| verb_spatial_random_f18 | 26.2 | 24.3 | 23.3 | **24.6%** |
| verb_spatial_random_f6 | 16.2 | 16.2 | 14.3 | **15.5%** |
| verb_spatial_stair_f12 | 26.7 | 28.6 | 25.2 | **26.8%** |
| verb_spatial_stair_f18 | 34.3 | 37.1 | 35.2 | **35.5%** |
| verb_spatial_stair_f6 | 23.3 | 27.1 | 22.9 | **24.4%** |
## spatial_size
| ckpt | s42 | s40 | s41 | 3-seed 均 |
|---|---|---|---|---|
| spatial_size_Lrandom_f12 | 38.1 | 30.0 | 33.3 | **33.8%** |
| spatial_size_Lrandom_f18 | 32.4 | 35.7 | 33.8 | **33.9%** |
| spatial_size_Lrandom_f6 | 24.3 | 21.0 | 24.8 | **23.3%** |
| spatial_size_random_f12 | 37.6 | 33.3 | 34.3 | **35.0%** |
| spatial_size_random_f18 | 27.6 | 30.5 | 28.1 | **28.7%** |
| spatial_size_random_f6 | 21.4 | 17.6 | 24.3 | **21.1%** |
| spatial_size_stair_f12 | 36.2 | 37.6 | 40.5 | **38.1%** |
| spatial_size_stair_f18 | 46.7 | 46.7 | 51.0 | **48.1%** |
## spatial_object
| ckpt | s42 | s40 | s41 | 3-seed 均 |
|---|---|---|---|---|
| spatial_object_Lrandom_f12 | 40.0 | 40.0 | 38.6 | **39.5%** |
| spatial_object_Lrandom_f18 | 34.8 | 31.4 | 32.9 | **33.0%** |
| spatial_object_random_f12 | 27.1 | 32.4 | 29.5 | **29.6%** |
| spatial_object_random_f18 | 34.3 | 36.7 | 32.4 | **34.4%** |
| spatial_object_random_f6 | 17.6 | 17.6 | 15.7 | **16.9%** |
| spatial_object_stair_f12 | 30.5 | 39.0 | 34.8 | **34.7%** |
| spatial_object_stair_f18 | 32.9 | 34.8 | 28.6 | **32.1%** |
| spatial_object_stair_f6 | 28.6 | 32.9 | 26.2 | **29.2%** |
## verb_size
| ckpt | s42 | s40 | s41 | 3-seed 均 |
|---|---|---|---|---|
| verb_size_Lrandom_f12 | 13.4 | 15.3 | 16.7 | **15.1%** |
| verb_size_Lrandom_f18 | 22.2 | 23.6 | 23.6 | **23.1%** |
| verb_size_Lrandom_f6 | 8.3 | 9.3 | 7.4 | **8.3%** |
| verb_size_random_f12 | 23.1 | 24.5 | 25.0 | **24.2%** |
| verb_size_random_f18 | 14.4 | 13.9 | 11.6 | **13.3%** |
| verb_size_random_f6 | 10.2 | 8.8 | 7.4 | **8.8%** |
| verb_size_stair1_f12 | 20.4 | 17.6 | 17.1 | **18.3%** |
| verb_size_stair1_f18 | 17.6 | 16.2 | 18.5 | **17.4%** |
---
# 二、GR00T all_factor (full-factor, pi0.5 对齐, 3-seed)
| ckpt | s42 | s40 | s41 | 3-seed 均 |
|---|---|---|---|---|
| all_factor_Lrandom_f50_n100 | 46.5 | 43.5 | 49.5 | **46.5%** |
| all_factor_Lrandom_f50_n200 | 44.0 | 43.0 | 36.0 | **41.0%** |
| all_factor_Lrandom_f50_n400 | 45.5 | 48.0 | 47.5 | **47.0%** |
| all_factor_Lrandom_n200 | 34.0 | 26.0 | 35.0 | **31.6%** |
| all_factor_Lrandom_n400 | 31.0 | 33.0 | 37.0 | **33.6%** |
| all_factor_Lrandom_n800 | 32.0 | 31.5 | 38.0 | **33.8%** |
| all_factor_stairoriginal2_n200 | 38.5 | 35.0 | 38.5 | **37.3%** |
| all_factor_stairverbsize_n200 | 36.5 | 32.5 | 38.0 | **35.6%** |
| all_factor_stairverbsize_n400 | 44.5 | 41.5 | 38.5 | **41.5%** |
| all_factor_stairverbsize_n800 | 29.0 | 31.5 | 32.0 | **30.8%** |
| all_factor_stairvss_f50_n200 | 40.0 | 40.5 | 44.5 | **41.6%** |
| all_factor_stairvss_f50_n400 | 42.0 | 43.0 | 43.5 | **42.8%** |
| all_factor_stairvss_f50_n800 | 42.5 | 45.5 | 51.5 | **46.5%** |
| all_factor_true_random_n200 | 36.0 | 31.0 | 34.5 | **33.8%** |
| all_factor_true_random_n400 | 40.5 | 38.0 | 36.0 | **38.1%** |
| all_factor_true_random_n800 | 41.5 | 38.5 | 44.0 | **41.3%** |
---
# 三、Conflict-experiment 双轴 env success (seed42, 200 ep)
每个实验两个因子的 success(模型把任务做对、且作用在正确因子目标上)。
| experiment | GR00T 因子A | GR00T 因子B | Genie 因子A | Genie 因子B |
|---|---|---|---|---|
| color_object | 15.0% | 14.0% | 11.7% | 6.7% |
| color_size | 47.0% | 29.5% | 1.5% | 0.0% |
| color_spatial | 5.5% | 39.5% | 10.5% | 38.5% |
| size_object | 18.5% | 29.5% | 0.0% | 0.0% |
| spatial_object | 9.0% | 22.0% | 1.5% | 16.2% |
| spatial_size | 1.0% | 25.0% | 30.5% | 18.5% |
| verb_color | 24.5% | 24.0% | 13.5% | 11.5% |
| verb_object | 8.0% | 31.5% | 4.9% | 3.2% |
| verb_size | 17.0% | 9.0% | 19.5% | 22.5% |
| verb_spatial | 38.5% | 4.0% | 7.0% | 14.5% |
---
# 四、VLM (Gemini-2.5-flash) FDR 对照
```
============================================================================================
Factor Dominance Rate (FDR) 三方对照 — FDR=(S_f1-S_f2)/(S_f1+S_f2), >0偏因子A <0偏因子B
env = 基于 ManiSkill 环境 success(每模型 200 episodes)
vlm = 基于 Gemini-2.5-flash 看视频判 factor_followed(每模型 400 视频/实验)
============================================================================================
experiment A/B env_GR00T env_genie vlm_GR00T vlm_genie
--------------------------------------------------------------------------------------------
color_object color/shape +0.034 +0.034 +0.228 +0.222
color_size color/size +0.229 +1.000 +0.524 +0.309
color_spatial color/spati -0.756 -0.571 +0.084 +0.365
size_object size/shape -0.229 +0.602 -0.241 -0.114
spatial_object spati/shape -0.419 -0.713 -0.095 -0.209
spatial_size spati/size -0.923 +0.245 +0.110 +0.237
verb_color verb/color +0.010 +0.080 -0.068 -0.220
verb_object verb/shape -0.595 -0.062 -0.253 -0.250
verb_size verb/size +0.308 -0.071 +0.251 +0.326
verb_spatial verb/spati +0.812 -0.349 -0.122 -0.142
--------------------------------------------------------------------------------------------
VLM 判定明细(N_f1 / N_f2 / neither|error,共400):
```
---
# 五、pi0 (openpi pi-zero) pair-grid (硬口径, 3-seed)
> 与 GR00T pair-grid 同口径(同色同形干扰项),但 sim_backend=cpu(pi0 server+GPU-sim 冲突)。注意 pi0 与 GR00T 推理栈不同,数值横向比 GR00T 仅供参考。
## pi0 — color_spatial
| ckpt | s42 | s40 | s41 | 3-seed 均 |
|---|---|---|---|---|
| color_spatial_Lrandom_f12 | 52.4 | 41.4 | 49.5 | **47.7%** |
| color_spatial_Lrandom_f18 | 53.8 | 41.0 | 48.6 | **47.8%** |
| color_spatial_Lrandom_f6 | 28.6 | 23.3 | 26.7 | **26.2%** |
| color_spatial_random_f12 | 38.6 | 32.4 | 37.6 | **36.2%** |
| color_spatial_random_f18 | 51.0 | 41.9 | 47.6 | **46.8%** |
| color_spatial_random_f6 | 27.6 | 21.4 | 23.3 | **24.1%** |
| color_spatial_stair_f12 | 49.0 | 38.1 | 42.4 | **43.1%** |
| color_spatial_stair_f18 | 60.0 | 49.0 | 55.7 | **54.9%** |
| color_spatial_stair_f6 | 31.0 | 24.8 | 28.6 | **28.1%** |
## pi0 — color_size
| ckpt | s42 | s40 | s41 | 3-seed 均 |
|---|---|---|---|---|
| color_size_Lrandom_f12 | 27.3 | - | - | 1/3(部分) |
| color_size_Lrandom_f18 | 30.6 | 29.2 | 27.3 | **29.0%** |
| color_size_Lrandom_f6 | 26.4 | - | - | 1/3(部分) |
| color_size_random_f12 | - | - | - | 0/3(部分) |
| color_size_random_f18 | 28.7 | 25.9 | 23.1 | **25.9%** |
| color_size_random_f6 | - | - | - | 0/3(部分) |
| color_size_stair_f18 | 26.4 | 28.2 | 24.1 | **26.2%** |
---
# 附:可复现配置(干扰项 / 口径明细)
## 公共设置(pair-grid 全实验)
- 环境:`VerbObjectColor-v1`(ManiSkill),obs=rgb,control=pd_joint_pos
- task_difficulty=**1.5**,sim/render_backend=**gpu**,max_episode_steps=**150**,replan_steps=**10**
- 每 seed:cells × reps,target≈210 episodes;seeds=**{42,40,41}**(3-seed 平均)
- 干扰项核心:**同色**(且多数同形 cube)干扰项,强制模型靠目标因子区分,而非靠颜色/形状走捷径
- spatial 锚点(xy,米)+ 抖动 ±0.012:`left(-0.10,0) right(0.10,0) middle(0,0) front(0,0.10) behind(0,-0.10)`
## color_size — HARD 口径
- verb=lift, shape=cube;指令 `"Lift the {size} {color} cube."`
- 干扰项 = 同色 cube,仅尺寸不同。(target_scale, [干扰scale...], 干扰数):
- small (0.72,[1.20],1) · large (1.34,[0.80],1) · smaller (0.82,[1.08],1) · larger (1.18,[0.92],1) · smallest (0.78,[1.00,1.24],**2**) · largest (1.26,[1.00,0.80],**2**)
## color_size — EASY 口径
- 同 HARD 但干扰项恒为 1 个、对比拉大 ~2×:
- small (0.65,[1.35],1) · large (1.40,[0.65],1) · smaller (0.70,[1.30],1) · larger (1.30,[0.70],1) · smallest (0.65,[1.40],1) · largest (1.40,[0.65],1)
## color_spatial — HARD 口径
- shape=cube,verb~{lift,grasp,push} 随机;指令 `"{Verb} the {color} cube {spatial_phrase}."`
- 干扰项 = 1 个**同色 cube**,放在**不同 spatial 锚点**;target_size_scale=1.0
## verb_spatial — HARD 口径
- shape=cube,color 每 cell 随机;指令 `"{Verb} the cube {spatial_phrase}."`
- 干扰项 = 1 个**同色 cube**,放在**不同 spatial 锚点**
## spatial_size — HARD 口径
- shape=cube,color&verb 随机;指令 `"{Verb} the {size} cube {spatial_phrase}."`
- 干扰项 = 1 个**同色 cube**,**不同 spatial + 不同尺寸**(目标偏小→干扰 scale=1.25;目标偏大→0.75)
## spatial_object — HARD 口径
- color&verb 随机;指令 `"{Verb} the {shape} {spatial_phrase}."`
- 干扰项 = 1 个**同色、不同形状**物体,放在**不同 spatial 锚点**
## verb_size — HARD 口径
- shape=cube,color 随机;指令 `"{Verb} the {size} cube."`
- 干扰项 = 同色 cube,仅尺寸不同(同 color_size HARD 的 HARD_SIZE 表)
## all_factor — full-factor(对齐 pi0.5)
- 单指令全因子采样;sample_n=200, sample_seed=42, 200 episodes/seed
- max_episode_steps=**500**, **no_distractor_prob=0.70**, 默认 difficulty, sim=gpu;seeds={40,41,42}
## pi0 pair-grid
- 与 GR00T pair-grid 同口径,但 **sim_backend=cpu**(pi0 server 与 GPU-sim 冲突);其余同上
|