baseline
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# 问题一：固定示例对比
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参考解为独立的大框半平面裁剪 + 精确直径/MEC；
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固定示例见 `examples/q1`，解析期望由 `tests/test_geometry*.py` 固化。
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| 算例 | 来源 | 参考状态 | 最优状态 | 基线状态 | D参考(m) | D最优(m) | D基线(m) | |ΔD|最优 | |ΔD|基线 | 覆盖参考 | 覆盖最优 | 覆盖基线 |
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| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
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| 三点交会 | examples/q1 | polygon | polygon | polygon | 26.99 | 26.99 | 21.21 | 0.00 | 5.77 | 否 | 否 | 是 |
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| 直径圆反例 | examples/q1 | polygon | polygon | polygon | 40.00 | 40.00 | 50.00 | 0.00 | 10.00 | 否 | 否 | 是 |
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| 近共线检测点 | examples/q1 | unbounded | unbounded | unbounded | — | — | — | — | — | — | — | — |
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| 零误差退化线段 | examples/q1 | segment | segment | point | 100.00 | 100.00 | 0.00 | 0.00 | 100.00 | 是 | 是 | 是 |
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| 不相容观测 | examples/q1 | empty | empty | empty | — | — | — | — | — | — | — | — |
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## 汇总
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| 指标 | 最优 | 基线 |
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| --- | --- | --- |
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| 状态判定准确率 | 100.0% | 80.0% |
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| 直径平均绝对误差 (m) | 0.000 | 7.886 |
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| 直径最大误差 (m) | 0.000 | 10.000 |
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| 覆盖判定准确率 | 100.0% | 33.3% |
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| 平均耗时 (ms) | 0.064 | 14.202 |
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# 问题一：随机交会算例对比
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参考解为独立的大框半平面裁剪 + 精确直径/MEC；
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固定示例见 `examples/q1`，解析期望由 `tests/test_geometry*.py` 固化。
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| 算例 | 来源 | 参考状态 | 最优状态 | 基线状态 | D参考(m) | D最优(m) | D基线(m) | |ΔD|最优 | |ΔD|基线 | 覆盖参考 | 覆盖最优 | 覆盖基线 |
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| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
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| 随机交会 | synthetic | polygon | polygon | polygon | 40.32 | 40.32 | 29.15 | 0.00 | 11.16 | 是 | 是 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 33.36 | 33.36 | 35.36 | 0.00 | 2.00 | 是 | 是 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 39.78 | 39.78 | 40.31 | 0.00 | 0.53 | 是 | 是 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 37.50 | 37.50 | 36.06 | 0.00 | 1.44 | 否 | 否 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 48.24 | 48.24 | 47.43 | 0.00 | 0.81 | 是 | 是 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 27.97 | 27.97 | 25.00 | 0.00 | 2.97 | 否 | 否 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 31.84 | 31.84 | 32.02 | 0.00 | 0.17 | 否 | 否 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 39.13 | 39.13 | 31.62 | 0.00 | 7.51 | 是 | 是 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 31.60 | 31.60 | 32.02 | 0.00 | 0.42 | 是 | 是 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 34.49 | 34.49 | 32.02 | 0.00 | 2.48 | 否 | 否 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 32.61 | 32.61 | 26.93 | 0.00 | 5.68 | 是 | 是 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 37.41 | 37.41 | 35.36 | 0.00 | 2.05 | 否 | 否 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 35.15 | 35.15 | 36.06 | 0.00 | 0.90 | 否 | 否 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 20.56 | 20.56 | 18.03 | 0.00 | 2.53 | 否 | 否 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 25.23 | 25.23 | 18.03 | 0.00 | 7.20 | 否 | 否 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 31.61 | 31.61 | 32.02 | 0.00 | 0.41 | 是 | 是 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 22.19 | 22.19 | 14.14 | 0.00 | 8.05 | 否 | 否 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 26.31 | 26.31 | 18.03 | 0.00 | 8.28 | 是 | 是 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 37.85 | 37.85 | 28.28 | 0.00 | 9.56 | 是 | 是 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 25.78 | 25.78 | 11.18 | 0.00 | 14.60 | 是 | 是 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 22.53 | 22.53 | 18.03 | 0.00 | 4.51 | 否 | 否 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 36.84 | 36.84 | 26.93 | 0.00 | 9.91 | 是 | 是 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 51.21 | 51.21 | 47.17 | 0.00 | 4.04 | 是 | 是 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 32.88 | 32.88 | 29.15 | 0.00 | 3.73 | 是 | 是 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 29.99 | 29.99 | 32.02 | 0.00 | 2.02 | 否 | 否 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 36.50 | 36.50 | 28.28 | 0.00 | 8.21 | 是 | 是 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 26.38 | 26.38 | 18.03 | 0.00 | 8.35 | 是 | 是 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 50.11 | 50.11 | 49.24 | 0.00 | 0.86 | 是 | 是 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 23.29 | 23.29 | 22.36 | 0.00 | 0.93 | 否 | 否 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 40.73 | 40.73 | 42.43 | 0.00 | 1.70 | 是 | 是 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 34.09 | 34.09 | 25.00 | 0.00 | 9.09 | 是 | 是 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 23.35 | 23.35 | 18.03 | 0.00 | 5.32 | 否 | 否 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 14.89 | 14.89 | 11.18 | 0.00 | 3.71 | 否 | 否 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 38.12 | 38.12 | 33.54 | 0.00 | 4.58 | 是 | 是 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 13.68 | 13.68 | 5.00 | 0.00 | 8.68 | 是 | 是 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 41.44 | 41.44 | 43.01 | 0.00 | 1.57 | 否 | 否 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 22.99 | 22.99 | 18.03 | 0.00 | 4.97 | 否 | 否 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 34.00 | 34.00 | 35.36 | 0.00 | 1.35 | 否 | 否 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 16.20 | 16.20 | 7.07 | 0.00 | 9.13 | 否 | 否 | 是 |
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| 随机交会 | synthetic | polygon | polygon | polygon | 26.90 | 26.90 | 25.00 | 0.00 | 1.90 | 否 | 否 | 是 |
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## 汇总
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| 指标 | 最优 | 基线 |
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| --- | --- | --- |
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| 状态判定准确率 | 100.0% | 100.0% |
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| 直径平均绝对误差 (m) | 0.000 | 4.583 |
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| 直径最大误差 (m) | 0.000 | 14.599 |
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| 覆盖判定准确率 | 100.0% | 52.5% |
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| 平均耗时 (ms) | 0.086 | 15.932 |
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# 问题二：第二检测点选择对比
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初始 ρ 为首次示向度候选集 K₁ 的最小包围半径；最坏后验按目标边界采样 × 读数区间端点统一评估。
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| 算例 | 方法 | 初始 ρ(m) | 第二点 q | 保证接收 | q 到 K₁ 最远(m) | 最坏后验 ρ'(m) | 收缩(m) | 移动(s) |
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| --- | --- | --- | --- | --- | --- | --- | --- | --- |
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| q2-4200 | optimal | 674.59 | (1257,89) | 是 | 907.09 | 54.45 | 620.13 | 181.42 |
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| q2-4200 | baseline_perp | 674.59 | (194,462) | 否 | 1679.16 | 76.22 | 598.36 | 200.00 |
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| q2-4200 | baseline_mec | 674.59 | (1173,-226) | 是 | 674.59 | 337.29 | 337.29 | 134.92 |
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| q2-4200 | reference | 674.59 | (1173,100) | 是 | 850.11 | 57.70 | 616.89 | 170.02 |
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| q2-4201 | optimal | 261.33 | (-1501,-348) | 是 | 461.91 | 13.55 | 247.78 | 92.38 |
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| q2-4201 | baseline_perp | 261.33 | (-782,-715) | 否 | 1131.68 | 27.22 | 234.11 | 200.00 |
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| q2-4201 | baseline_mec | 261.33 | (-1578,-63) | 是 | 261.33 | 130.67 | 130.67 | 52.27 |
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| q2-4201 | reference | 261.33 | (-1393,-432) | 是 | 527.03 | 14.98 | 246.36 | 105.41 |
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| q2-4202 | optimal | 591.09 | (-1126,-861) | 是 | 869.01 | 37.92 | 553.17 | 173.80 |
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| q2-4202 | baseline_perp | 591.09 | (408,-1235) | 否 | 1561.73 | 64.57 | 526.52 | 200.00 |
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| q2-4202 | baseline_mec | 591.09 | (-731,-967) | 是 | 591.09 | 295.54 | 295.54 | 118.22 |
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| q2-4202 | reference | 591.09 | (-1038,-865) | 是 | 788.83 | 46.22 | 544.86 | 157.77 |
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| q2-4203 | optimal | 326.92 | (1145,-1745) | 是 | 683.58 | 17.13 | 309.79 | 136.72 |
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| q2-4203 | baseline_perp | 326.92 | (1837,-1523) | 否 | 1204.35 | 32.99 | 293.93 | 200.00 |
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| q2-4203 | baseline_mec | 326.92 | (788,-1388) | 是 | 326.92 | 163.46 | 163.46 | 65.38 |
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| q2-4203 | reference | 326.92 | (1125,-1725) | 是 | 657.98 | 16.90 | 310.02 | 131.60 |
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| q2-4204 | optimal | 750.20 | (-401,208) | 是 | 876.74 | 91.60 | 658.60 | 175.35 |
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| q2-4204 | baseline_perp | 750.20 | (-1541,302) | 否 | 1817.48 | 90.79 | 659.41 | 200.00 |
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| q2-4204 | baseline_mec | 750.20 | (-336,-34) | 是 | 750.20 | 375.10 | 375.10 | 150.04 |
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| q2-4204 | reference | 750.20 | (-336,216) | 是 | 923.80 | 92.25 | 657.95 | 184.76 |
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| q2-4205 | optimal | 750.14 | (-503,21) | 是 | 881.59 | 91.10 | 659.04 | 176.32 |
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| q2-4205 | baseline_perp | 750.14 | (-612,-1470) | 否 | 1817.36 | 90.78 | 659.36 | 200.00 |
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| q2-4205 | baseline_mec | 750.14 | (-568,-220) | 是 | 750.14 | 375.08 | 375.06 | 150.03 |
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| q2-4205 | reference | 750.14 | (-568,30) | 是 | 927.74 | 92.25 | 657.89 | 185.55 |
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| q2-4206 | optimal | 750.12 | (216,677) | 是 | 892.00 | 90.96 | 659.16 | 178.40 |
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| q2-4206 | baseline_perp | 750.12 | (1592,1266) | 否 | 1817.31 | 90.77 | 659.34 | 200.00 |
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| q2-4206 | baseline_mec | 750.12 | (457,742) | 是 | 750.12 | 375.10 | 375.02 | 150.02 |
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| q2-4206 | reference | 750.12 | (207,742) | 是 | 838.72 | 94.21 | 655.91 | 167.74 |
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| q2-4207 | optimal | 750.12 | (1205,476) | 是 | 899.09 | 90.85 | 659.27 | 179.82 |
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| q2-4207 | baseline_perp | 750.12 | (578,1465) | 否 | 1817.31 | 90.78 | 659.34 | 200.00 |
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| q2-4207 | baseline_mec | 750.12 | (1028,299) | 是 | 750.12 | 375.09 | 375.03 | 150.02 |
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| q2-4207 | reference | 750.12 | (1028,49) | 是 | 852.52 | 92.97 | 657.15 | 170.50 |
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| q2-4208 | optimal | 750.19 | (-1409,-294) | 是 | 901.20 | 90.75 | 659.44 | 180.24 |
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| q2-4208 | baseline_perp | 750.19 | (-8,239) | 否 | 1817.46 | 90.79 | 659.40 | 200.00 |
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| q2-4208 | baseline_mec | 750.19 | (-1167,-229) | 是 | 750.19 | 375.10 | 375.09 | 150.04 |
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| q2-4208 | reference | 750.19 | (-1417,-229) | 是 | 849.54 | 93.05 | 657.14 | 169.91 |
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| q2-4209 | optimal | 750.20 | (463,849) | 是 | 849.70 | 93.03 | 657.17 | 169.94 |
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| q2-4209 | baseline_perp | 750.20 | (-621,1100) | 否 | 1817.43 | 90.79 | 659.41 | 200.00 |
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| q2-4209 | baseline_mec | 750.20 | (527,607) | 是 | 750.20 | 375.10 | 375.10 | 150.04 |
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| q2-4209 | reference | 750.20 | (527,857) | 是 | 901.34 | 90.74 | 659.46 | 180.27 |
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| q2-4210 | optimal | 706.03 | (-429,1151) | 是 | 915.53 | 63.69 | 642.34 | 183.11 |
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| q2-4210 | baseline_perp | 706.03 | (-206,15) | 否 | 1722.00 | 80.64 | 625.39 | 200.00 |
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| q2-4210 | baseline_mec | 706.03 | (-145,1227) | 是 | 706.03 | 353.02 | 353.02 | 141.21 |
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| q2-4210 | reference | 706.03 | (-366,1080) | 是 | 830.65 | 72.40 | 633.63 | 166.13 |
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| q2-4211 | optimal | 750.20 | (-619,-443) | 是 | 901.34 | 90.74 | 659.46 | 180.27 |
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| q2-4211 | baseline_perp | 750.20 | (-379,1037) | 否 | 1817.47 | 90.79 | 659.41 | 200.00 |
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| q2-4211 | baseline_mec | 750.20 | (-554,-202) | 是 | 750.20 | 375.10 | 375.10 | 150.04 |
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| q2-4211 | reference | 750.20 | (-554,-451) | 是 | 943.43 | 94.71 | 655.49 | 188.69 |
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| q2-4212 | optimal | 750.13 | (343,-10) | 是 | 905.38 | 90.90 | 659.23 | 181.08 |
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| q2-4212 | baseline_perp | 750.13 | (1486,-980) | 否 | 1817.34 | 90.78 | 659.35 | 200.00 |
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| q2-4212 | baseline_mec | 750.13 | (520,-187) | 是 | 750.13 | 375.09 | 375.04 | 150.03 |
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| q2-4212 | reference | 750.13 | (520,-437) | 是 | 845.04 | 93.65 | 656.48 | 169.01 |
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| q2-4213 | optimal | 750.12 | (-347,-795) | 是 | 859.45 | 92.44 | 657.68 | 171.89 |
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| q2-4213 | baseline_perp | 750.12 | (-1650,-75) | 否 | 1817.31 | 90.77 | 659.34 | 200.00 |
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| q2-4213 | baseline_mec | 750.12 | (-524,-618) | 是 | 750.12 | 375.09 | 375.03 | 150.02 |
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| q2-4213 | reference | 750.12 | (-524,-368) | 是 | 893.01 | 90.88 | 659.24 | 178.60 |
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| q2-4214 | optimal | 750.16 | (623,-1142) | 是 | 906.31 | 90.87 | 659.29 | 181.26 |
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| q2-4214 | baseline_perp | 750.16 | (-445,-639) | 否 | 1817.36 | 90.78 | 659.38 | 200.00 |
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| q2-4214 | baseline_mec | 750.16 | (559,-1383) | 是 | 750.16 | 375.09 | 375.07 | 150.03 |
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| q2-4214 | reference | 750.16 | (559,-1134) | 是 | 855.60 | 92.58 | 657.58 | 171.12 |
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| q2-4215 | optimal | 559.27 | (-1338,120) | 是 | 820.56 | 35.56 | 523.71 | 164.11 |
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| q2-4215 | baseline_perp | 559.27 | (-731,-1350) | 否 | 1513.40 | 59.96 | 499.32 | 200.00 |
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| q2-4215 | baseline_mec | 559.27 | (-1224,-306) | 是 | 559.27 | 279.64 | 279.64 | 111.85 |
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| q2-4215 | reference | 559.27 | (-1444,-636) | 是 | 828.17 | 35.86 | 523.42 | 165.63 |
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| q2-4216 | optimal | 725.32 | (-758,-1062) | 是 | 869.88 | 65.59 | 659.73 | 173.97 |
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| q2-4216 | baseline_perp | 725.32 | (-669,40) | 否 | 1747.41 | 79.80 | 645.52 | 200.00 |
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| q2-4216 | baseline_mec | 725.32 | (-1023,-1133) | 是 | 725.32 | 362.66 | 362.66 | 145.06 |
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| q2-4216 | reference | 725.32 | (-749,-1133) | 是 | 919.99 | 63.67 | 661.65 | 184.00 |
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| q2-4217 | optimal | 750.16 | (-1472,727) | 是 | 848.85 | 93.13 | 657.03 | 169.77 |
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| q2-4217 | baseline_perp | 750.16 | (10,819) | 否 | 1817.41 | 90.78 | 659.38 | 200.00 |
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| q2-4217 | baseline_mec | 750.16 | (-1231,663) | 是 | 750.16 | 375.09 | 375.07 | 150.03 |
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| q2-4217 | reference | 750.16 | (-1481,663) | 是 | 900.62 | 90.77 | 659.39 | 180.12 |
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| q2-4218 | optimal | 750.18 | (-332,-300) | 是 | 864.09 | 92.27 | 657.91 | 172.82 |
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| q2-4218 | baseline_perp | 750.18 | (-1821,-299) | 否 | 1817.39 | 90.78 | 659.39 | 200.00 |
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| q2-4218 | baseline_mec | 750.18 | (-573,-235) | 是 | 750.18 | 375.09 | 375.08 | 150.04 |
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| q2-4218 | reference | 750.18 | (-323,-235) | 是 | 913.40 | 91.48 | 658.69 | 182.68 |
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| q2-4219 | optimal | 750.13 | (-75,786) | 是 | 868.14 | 91.76 | 658.37 | 173.63 |
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| q2-4219 | baseline_perp | 750.13 | (-100,-705) | 否 | 1817.34 | 90.78 | 659.35 | 200.00 |
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| q2-4219 | baseline_mec | 750.13 | (-140,544) | 是 | 750.13 | 375.09 | 375.04 | 150.03 |
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| q2-4219 | reference | 750.13 | (-140,794) | 是 | 916.75 | 91.35 | 658.78 | 183.35 |
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| q2-4220 | optimal | 750.13 | (-142,237) | 是 | 865.60 | 92.06 | 658.07 | 173.12 |
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| q2-4220 | baseline_perp | 750.13 | (-1191,-184) | 否 | 1817.34 | 90.78 | 659.35 | 200.00 |
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| q2-4220 | baseline_mec | 750.13 | (35,60) | 是 | 750.13 | 375.09 | 375.04 | 150.03 |
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| q2-4220 | reference | 750.13 | (285,60) | 是 | 887.39 | 90.95 | 659.18 | 177.48 |
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| q2-4221 | optimal | 750.12 | (537,-636) | 是 | 859.18 | 92.47 | 657.65 | 171.84 |
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| q2-4221 | baseline_perp | 750.12 | (-232,638) | 否 | 1817.32 | 90.78 | 659.35 | 200.00 |
|
||||
| q2-4221 | baseline_mec | 750.12 | (472,-395) | 是 | 750.12 | 375.09 | 375.03 | 150.02 |
|
||||
| q2-4221 | reference | 750.12 | (472,-644) | 是 | 801.14 | 98.78 | 651.34 | 160.23 |
|
||||
| q2-4222 | optimal | 672.85 | (1340,149) | 是 | 896.12 | 46.69 | 626.15 | 179.22 |
|
||||
| q2-4222 | baseline_perp | 672.85 | (461,-526) | 否 | 1662.43 | 70.95 | 601.90 | 200.00 |
|
||||
| q2-4222 | baseline_mec | 672.85 | (1571,-82) | 是 | 672.85 | 336.42 | 336.42 | 134.57 |
|
||||
| q2-4222 | reference | 672.85 | (1326,82) | 是 | 830.57 | 53.42 | 619.43 | 166.11 |
|
||||
| q2-4223 | optimal | 395.70 | (-1736,-787) | 是 | 696.84 | 21.22 | 374.48 | 139.37 |
|
||||
| q2-4223 | baseline_perp | 395.70 | (-1461,-1548) | 否 | 1286.11 | 39.72 | 355.98 | 200.00 |
|
||||
| q2-4223 | baseline_mec | 395.70 | (-1416,-467) | 是 | 395.70 | 197.85 | 197.85 | 79.14 |
|
||||
| q2-4223 | reference | 395.70 | (-1416,-14) | 是 | 716.03 | 20.83 | 374.87 | 143.21 |
|
||||
| q2-4224 | optimal | 750.16 | (-899,669) | 是 | 888.47 | 90.87 | 659.29 | 177.69 |
|
||||
| q2-4224 | baseline_perp | 750.16 | (467,1281) | 否 | 1817.40 | 90.78 | 659.38 | 200.00 |
|
||||
| q2-4224 | baseline_mec | 750.16 | (-657,734) | 是 | 750.16 | 375.09 | 375.07 | 150.03 |
|
||||
| q2-4224 | reference | 750.16 | (-907,734) | 是 | 834.61 | 94.50 | 655.66 | 166.92 |
|
||||
| q2-4225 | optimal | 750.12 | (-305,-294) | 是 | 866.51 | 91.95 | 658.17 | 173.30 |
|
||||
| q2-4225 | baseline_perp | 750.12 | (-1064,-1577) | 否 | 1817.31 | 90.77 | 659.34 | 200.00 |
|
||||
| q2-4225 | baseline_mec | 750.12 | (-482,-470) | 是 | 750.12 | 375.10 | 375.02 | 150.02 |
|
||||
| q2-4225 | reference | 750.12 | (-732,-470) | 是 | 886.54 | 91.02 | 659.10 | 177.31 |
|
||||
| q2-4226 | optimal | 750.12 | (587,389) | 是 | 898.38 | 90.90 | 659.22 | 179.68 |
|
||||
| q2-4226 | baseline_perp | 750.12 | (1757,433) | 否 | 1817.31 | 90.77 | 659.34 | 200.00 |
|
||||
| q2-4226 | baseline_mec | 750.12 | (523,630) | 是 | 750.12 | 375.11 | 375.01 | 150.02 |
|
||||
| q2-4226 | reference | 750.12 | (523,380) | 是 | 941.12 | 94.47 | 655.65 | 188.22 |
|
||||
| q2-4227 | optimal | 527.91 | (711,-1627) | 是 | 843.99 | 29.98 | 497.92 | 168.80 |
|
||||
| q2-4227 | baseline_perp | 527.91 | (1503,-1122) | 否 | 1466.90 | 55.63 | 472.28 | 200.00 |
|
||||
| q2-4227 | baseline_mec | 527.91 | (377,-1293) | 是 | 527.91 | 263.95 | 263.95 | 105.58 |
|
||||
| q2-4227 | reference | 527.91 | (-95,-1293) | 是 | 819.70 | 30.74 | 497.17 | 163.94 |
|
||||
| q2-4228 | optimal | 750.12 | (-160,534) | 是 | 892.39 | 90.93 | 659.19 | 178.48 |
|
||||
| q2-4228 | baseline_perp | 750.12 | (20,2020) | 否 | 1817.31 | 90.77 | 659.34 | 200.00 |
|
||||
| q2-4228 | baseline_mec | 750.12 | (-96,775) | 是 | 750.12 | 375.11 | 375.01 | 150.02 |
|
||||
| q2-4228 | reference | 750.12 | (-96,525) | 是 | 936.39 | 93.58 | 656.54 | 187.28 |
|
||||
| q2-4229 | optimal | 750.20 | (455,-883) | 是 | 876.70 | 91.34 | 658.86 | 175.34 |
|
||||
| q2-4229 | baseline_perp | 750.20 | (-684,-787) | 否 | 1817.44 | 90.79 | 659.41 | 200.00 |
|
||||
| q2-4229 | baseline_mec | 750.20 | (519,-1124) | 是 | 750.20 | 375.10 | 375.10 | 150.04 |
|
||||
| q2-4229 | reference | 750.20 | (519,-874) | 是 | 923.76 | 91.91 | 658.30 | 184.75 |
|
||||
|
||||
## 逐方法汇总
|
||||
|
||||
| 方法 | 保证接收率 | 最坏后验均值(m) | 中位(m) | 平均收缩(m) | 终值比 ρ'/ρ | 移动均值(s) |
|
||||
| --- | --- | --- | --- | --- | --- | --- |
|
||||
| optimal | 100.0% | 73.89 | 90.90 | 607.58 | 0.104 | 170.44 |
|
||||
| baseline_perp | 0.0% | 80.11 | 90.78 | 601.36 | 0.116 | 200.00 |
|
||||
| baseline_mec | 100.0% | 340.75 | 375.09 | 340.72 | 0.500 | 136.29 |
|
||||
| reference | 100.0% | 75.63 | 91.35 | 605.84 | 0.106 | 170.28 |
|
||||
|
||||
初始 ρ 均值：681.47 m
|
||||
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@@ -0,0 +1,75 @@
|
||||
# 问题三：全向闭环配对对比（core 基准集）
|
||||
|
||||
## 逐场景明细
|
||||
|
||||
| scene | sources | variant | cleared | T(s) | 检测 | 请求 | 位移(m) | 后备清除 | 墙钟(s) | 有效 |
|
||||
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
|
||||
| q3-core-s100-n10 | 10 | optimal | 10/10 | 2563.0 | 109 | 119 | 9330.1 | 0 | 0.71 | ✔ |
|
||||
| q3-core-s100-n10 | 10 | seven | 10/10 | 4465.5 | 102 | 112 | 19057.6 | 0 | 1.10 | ✔ |
|
||||
| q3-core-s100-n10 | 10 | baseline | 10/10 | 15309.6 | 564 | 574 | 59457.9 | 0 | 1.16 | ✔ |
|
||||
| q3-core-s100-n13 | 13 | optimal | 13/13 | 3120.8 | 114 | 127 | 11914.1 | 0 | 0.70 | ✔ |
|
||||
| q3-core-s100-n13 | 13 | seven | 13/13 | 5216.0 | 96 | 109 | 22919.8 | 0 | 1.39 | ✔ |
|
||||
| q3-core-s100-n13 | 13 | baseline | 13/13 | 16205.3 | 450 | 463 | 67311.6 | 0 | 1.47 | ✔ |
|
||||
| q3-core-s100-n16 | 16 | optimal | 16/16 | 3618.1 | 113 | 129 | 14355.4 | 0 | 0.83 | ✔ |
|
||||
| q3-core-s100-n16 | 16 | seven | 16/16 | 5978.8 | 96 | 112 | 26653.8 | 0 | 1.63 | ✔ |
|
||||
| q3-core-s100-n16 | 16 | baseline | 16/16 | 13180.4 | 254 | 270 | 58011.9 | 0 | 1.82 | ✔ |
|
||||
| q3-core-s101-n10 | 10 | optimal | 10/10 | 3101.7 | 119 | 129 | 11723.5 | 0 | 0.68 | ✔ |
|
||||
| q3-core-s101-n10 | 10 | seven | 10/10 | 4498.1 | 107 | 117 | 19065.6 | 0 | 1.07 | ✔ |
|
||||
| q3-core-s101-n10 | 10 | baseline | 10/10 | 15552.8 | 545 | 555 | 61248.9 | 0 | 1.10 | ✔ |
|
||||
| q3-core-s101-n13 | 13 | optimal | 13/13 | 2943.3 | 112 | 125 | 11106.4 | 0 | 0.83 | ✔ |
|
||||
| q3-core-s101-n13 | 13 | seven | 13/13 | 5390.3 | 101 | 114 | 23656.4 | 0 | 1.42 | ✔ |
|
||||
| q3-core-s101-n13 | 13 | baseline | 13/13 | 16620.6 | 452 | 465 | 69338.1 | 0 | 1.60 | ✔ |
|
||||
| q3-core-s101-n16 | 16 | optimal | 16/16 | 3560.0 | 99 | 115 | 14469.9 | 0 | 0.81 | ✔ |
|
||||
| q3-core-s101-n16 | 16 | seven | 16/16 | 6462.4 | 92 | 108 | 29211.8 | 0 | 1.75 | ✔ |
|
||||
| q3-core-s101-n16 | 16 | baseline | 16/16 | 13434.4 | 260 | 276 | 59121.8 | 0 | 1.84 | ✔ |
|
||||
| q3-core-s102-n10 | 10 | optimal | 10/10 | 2916.0 | 125 | 135 | 10634.8 | 0 | 0.57 | ✔ |
|
||||
| q3-core-s102-n10 | 10 | seven | 10/10 | 5411.3 | 118 | 128 | 23326.6 | 0 | 1.22 | ✔ |
|
||||
| q3-core-s102-n10 | 10 | baseline | 10/10 | 15015.5 | 613 | 623 | 56517.5 | 0 | 1.13 | ✔ |
|
||||
| q3-core-s102-n13 | 13 | optimal | 13/13 | 3039.5 | 122 | 135 | 11242.3 | 0 | 0.71 | ✔ |
|
||||
| q3-core-s102-n13 | 13 | seven | 13/13 | 5209.5 | 112 | 125 | 22407.3 | 0 | 1.36 | ✔ |
|
||||
| q3-core-s102-n13 | 13 | baseline | 13/13 | 16062.8 | 450 | 463 | 66603.8 | 0 | 1.43 | ✔ |
|
||||
| q3-core-s102-n16 | 16 | optimal | 16/16 | 3266.2 | 119 | 135 | 12441.1 | 0 | 0.68 | ✔ |
|
||||
| q3-core-s102-n16 | 16 | seven | 16/16 | 5549.9 | 97 | 113 | 24489.6 | 0 | 1.65 | ✔ |
|
||||
| q3-core-s102-n16 | 16 | baseline | 16/16 | 13146.4 | 282 | 298 | 57012.1 | 0 | 1.72 | ✔ |
|
||||
| q3-core-s103-n10 | 10 | optimal | 10/10 | 2847.8 | 112 | 122 | 10684.1 | 0 | 0.67 | ✔ |
|
||||
| q3-core-s103-n10 | 10 | seven | 10/10 | 4877.3 | 110 | 120 | 20886.4 | 0 | 1.19 | ✔ |
|
||||
| q3-core-s103-n10 | 10 | baseline | 10/10 | 14895.2 | 550 | 560 | 57815.9 | 0 | 1.20 | ✔ |
|
||||
| q3-core-s103-n13 | 13 | optimal | 13/13 | 3339.9 | 114 | 127 | 13024.4 | 0 | 0.70 | ✔ |
|
||||
| q3-core-s103-n13 | 13 | seven | 13/13 | 5344.6 | 102 | 115 | 23373.1 | 0 | 1.21 | ✔ |
|
||||
| q3-core-s103-n13 | 13 | baseline | 13/13 | 16691.4 | 501 | 514 | 68212.0 | 0 | 1.47 | ✔ |
|
||||
| q3-core-s103-n16 | 16 | optimal | 16/16 | 3378.8 | 99 | 115 | 13559.2 | 0 | 0.86 | ✔ |
|
||||
| q3-core-s103-n16 | 16 | seven | 16/16 | 5526.4 | 87 | 103 | 24681.8 | 0 | 1.73 | ✔ |
|
||||
| q3-core-s103-n16 | 16 | baseline | 16/16 | 12627.8 | 256 | 272 | 55189.0 | 0 | 1.81 | ✔ |
|
||||
| q3-core-s104-n10 | 10 | optimal | 10/10 | 3317.0 | 115 | 125 | 12950.2 | 0 | 0.64 | ✔ |
|
||||
| q3-core-s104-n10 | 10 | seven | 10/10 | 4915.9 | 105 | 115 | 21219.3 | 0 | 1.00 | ✔ |
|
||||
| q3-core-s104-n10 | 10 | baseline | 10/10 | 15302.4 | 549 | 559 | 59887.2 | 0 | 1.18 | ✔ |
|
||||
| q3-core-s104-n13 | 13 | optimal | 13/13 | 3085.2 | 99 | 112 | 12176.2 | 0 | 0.70 | ✔ |
|
||||
| q3-core-s104-n13 | 13 | seven | 13/13 | 5437.5 | 97 | 110 | 24012.7 | 0 | 1.47 | ✔ |
|
||||
| q3-core-s104-n13 | 13 | baseline | 13/13 | 16278.7 | 444 | 457 | 67868.5 | 0 | 1.55 | ✔ |
|
||||
| q3-core-s104-n16 | 16 | optimal | 16/16 | 3057.8 | 85 | 101 | 12379.1 | 0 | 0.76 | ✔ |
|
||||
| q3-core-s104-n16 | 16 | seven | 16/16 | 5340.9 | 85 | 101 | 23799.8 | 0 | 1.65 | ✔ |
|
||||
| q3-core-s104-n16 | 16 | baseline | 16/16 | 12872.6 | 224 | 240 | 57378.0 | 0 | 1.83 | ✔ |
|
||||
| q3-core-s105-n10 | 10 | optimal | 10/10 | 2933.1 | 108 | 118 | 11220.4 | 0 | 0.70 | ✔ |
|
||||
| q3-core-s105-n10 | 10 | seven | 10/10 | 4370.8 | 107 | 117 | 18433.9 | 0 | 1.08 | ✔ |
|
||||
| q3-core-s105-n10 | 10 | baseline | 10/10 | 15247.7 | 579 | 589 | 58688.4 | 0 | 1.12 | ✔ |
|
||||
| q3-core-s105-n13 | 13 | optimal | 13/13 | 3645.3 | 122 | 135 | 14331.4 | 0 | 0.79 | ✔ |
|
||||
| q3-core-s105-n13 | 13 | seven | 13/13 | 6311.3 | 104 | 117 | 28171.5 | 0 | 1.41 | ✔ |
|
||||
| q3-core-s105-n13 | 13 | baseline | 13/13 | 16509.4 | 485 | 498 | 67791.8 | 0 | 1.51 | ✔ |
|
||||
| q3-core-s105-n16 | 16 | optimal | 16/16 | 3663.7 | 114 | 130 | 14543.5 | 0 | 0.80 | ✔ |
|
||||
| q3-core-s105-n16 | 16 | seven | 16/16 | 6204.3 | 97 | 113 | 27776.7 | 0 | 1.55 | ✔ |
|
||||
| q3-core-s105-n16 | 16 | baseline | 16/16 | 13889.0 | 292 | 308 | 60450.1 | 0 | 1.85 | ✔ |
|
||||
|
||||
## 逐方法汇总
|
||||
|
||||
| 方法 | 有效局 | 全清率 | 全清对数 | 缺席误判 | T 均值(s) | T 中位(s) | T 最大(s) | 检测均值 | 请求均值 | 位移均值(m) | 后备清除均值 | 墙钟均值(s) |
|
||||
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
|
||||
| optimal | 18/18 | 1.00 | 18 | 0 | 3188.7 | 3111.3 | 3663.7 | 111.1 | 124.1 | 12338.1 | 0.00 | 0.73 |
|
||||
| seven | 18/18 | 1.00 | 18 | 0 | 5361.7 | 5367.5 | 6462.4 | 100.8 | 113.8 | 23508.0 | 0.00 | 1.38 |
|
||||
| baseline | 18/18 | 1.00 | 18 | 0 | 14935.7 | 15275.1 | 16691.4 | 430.6 | 443.6 | 61550.2 | 0.00 | 1.49 |
|
||||
|
||||
## 相对基线的配对变化（虚拟时间）
|
||||
|
||||
| 配对 | 均值变化 | 中位变化 | 更快场景 | 双方均有效 |
|
||||
| --- | --- | --- | --- | --- |
|
||||
| optimal_vs_baseline | -78.4% | -80.0% | 18/18 | 18 |
|
||||
| seven_vs_baseline | -63.7% | -66.9% | 18/18 | 18 |
|
||||
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,56 @@
|
||||
# 问题四：混合源闭环配对对比（core+boundary 基准集）
|
||||
|
||||
## 逐场景明细
|
||||
|
||||
| scene | sources | variant | cleared | T(s) | 检测 | 请求 | 位移(m) | 后备清除 | 墙钟(s) | 有效 |
|
||||
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
|
||||
| q4-boundary-n10-d5 | 10 | optimal | 10/10 | 10269.5 | 488 | 540 | 36107.7 | 44 | 2.53 | ✔ |
|
||||
| q4-boundary-n10-d5 | 10 | baseline_grid | 6/10 | 17632.7 | 735 | 741 | 66308.6 | 0 | 5.04 | ✘ |
|
||||
| q4-boundary-n10-d5 | 10 | baseline | 5/10 | 3128.1 | 135 | 140 | 11530.4 | 0 | 0.48 | ✘ |
|
||||
| q4-boundary-n16-d8 | 16 | optimal | 16/16 | 12081.1 | 421 | 626 | 44820.7 | 190 | 3.54 | ✔ |
|
||||
| q4-boundary-n16-d8 | 16 | baseline_grid | 9/16 | 20457.9 | 623 | 632 | 83969.3 | 0 | 8.71 | ✘ |
|
||||
| q4-boundary-n16-d8 | 16 | baseline | 8/16 | 3558.7 | 149 | 157 | 13173.5 | 0 | 0.51 | ✘ |
|
||||
| q4-core-s200-n10-d3 | 10 | optimal | 10/10 | 8718.7 | 402 | 412 | 31508.6 | 0 | 7.61 | ✔ |
|
||||
| q4-core-s200-n10-d3 | 10 | baseline_grid | 9/10 | 16546.8 | 576 | 585 | 65379.2 | 0 | 2.52 | ✘ |
|
||||
| q4-core-s200-n10-d3 | 10 | baseline | 10/10 | 3354.1 | 116 | 126 | 13100.5 | 0 | 0.66 | ✘ |
|
||||
| q4-core-s200-n13-d6 | 13 | optimal | 13/13 | 8808.4 | 332 | 347 | 33967.1 | 3 | 2.71 | ✔ |
|
||||
| q4-core-s200-n13-d6 | 13 | baseline_grid | 7/13 | 18438.3 | 529 | 536 | 76651.4 | 0 | 8.12 | ✘ |
|
||||
| q4-core-s200-n13-d6 | 13 | baseline | 11/13 | 3264.4 | 111 | 122 | 12761.9 | 0 | 0.69 | ✘ |
|
||||
| q4-core-s200-n16-d8 | 16 | optimal | 16/16 | 7629.2 | 267 | 283 | 29970.8 | 0 | 2.77 | ✔ |
|
||||
| q4-core-s200-n16-d8 | 16 | baseline_grid | 10/16 | 18871.3 | 526 | 536 | 78861.6 | 0 | 8.97 | ✘ |
|
||||
| q4-core-s200-n16-d8 | 16 | baseline | 12/16 | 4026.1 | 143 | 155 | 15645.6 | 0 | 1.84 | ✘ |
|
||||
| q4-core-s201-n10-d3 | 10 | optimal | 10/10 | 8514.0 | 380 | 391 | 31129.9 | 2 | 1.94 | ✔ |
|
||||
| q4-core-s201-n10-d3 | 10 | baseline_grid | 7/10 | 16779.7 | 624 | 631 | 65293.4 | 0 | 5.42 | ✘ |
|
||||
| q4-core-s201-n10-d3 | 10 | baseline | 7/10 | 2823.3 | 120 | 127 | 10391.4 | 0 | 0.61 | ✘ |
|
||||
| q4-core-s201-n13-d6 | 13 | optimal | 13/13 | 9183.0 | 325 | 338 | 36095.1 | 0 | 2.47 | ✔ |
|
||||
| q4-core-s201-n13-d6 | 13 | baseline_grid | 8/13 | 19390.8 | 584 | 592 | 79678.9 | 0 | 4.29 | ✘ |
|
||||
| q4-core-s201-n13-d6 | 13 | baseline | 11/13 | 4965.2 | 143 | 165 | 20260.8 | 0 | 1.09 | ✘ |
|
||||
| q4-core-s201-n16-d8 | 16 | optimal | 16/16 | 8129.4 | 263 | 279 | 32667.0 | 0 | 3.29 | ✔ |
|
||||
| q4-core-s201-n16-d8 | 16 | baseline_grid | 9/16 | 19845.0 | 495 | 504 | 84765.2 | 0 | 10.53 | ✘ |
|
||||
| q4-core-s201-n16-d8 | 16 | baseline | 13/16 | 4759.1 | 125 | 138 | 19835.5 | 0 | 1.85 | ✘ |
|
||||
| q4-core-s202-n10-d3 | 10 | optimal | 10/10 | 8803.3 | 420 | 430 | 31426.3 | 0 | 2.16 | ✔ |
|
||||
| q4-core-s202-n10-d3 | 10 | baseline_grid | 7/10 | 17220.0 | 669 | 676 | 66144.9 | 0 | 4.67 | ✘ |
|
||||
| q4-core-s202-n10-d3 | 10 | baseline | 7/10 | 3646.2 | 135 | 142 | 14105.9 | 0 | 0.66 | ✘ |
|
||||
| q4-core-s202-n13-d6 | 13 | optimal | 13/13 | 9630.4 | 347 | 367 | 37652.0 | 10 | 3.09 | ✔ |
|
||||
| q4-core-s202-n13-d6 | 13 | baseline_grid | 10/13 | 16443.2 | 498 | 508 | 67316.3 | 0 | 1.92 | ✘ |
|
||||
| q4-core-s202-n13-d6 | 13 | baseline | 13/13 | 4219.3 | 123 | 137 | 17136.7 | 0 | 0.75 | ✘ |
|
||||
| q4-core-s202-n16-d8 | 16 | optimal | 16/16 | 8001.5 | 267 | 305 | 31602.7 | 24 | 3.52 | ✔ |
|
||||
| q4-core-s202-n16-d8 | 16 | baseline_grid | 12/16 | 18345.2 | 452 | 464 | 78265.8 | 0 | 8.12 | ✘ |
|
||||
| q4-core-s202-n16-d8 | 16 | baseline | 13/16 | 5054.4 | 152 | 165 | 20561.9 | 0 | 1.98 | ✘ |
|
||||
|
||||
## 逐方法汇总
|
||||
|
||||
| 方法 | 有效局 | 全清率 | 全清对数 | 缺席误判 | T 均值(s) | T 中位(s) | T 最大(s) | 检测均值 | 请求均值 | 位移均值(m) | 后备清除均值 | 墙钟均值(s) |
|
||||
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
|
||||
| optimal | 11/11 | 1.00 | 11 | 0 | 9069.9 | 8803.3 | 12081.1 | 355.6 | 392.5 | 34268.0 | 24.82 | 3.24 |
|
||||
| baseline_grid | 0/11 | 0.67 | 0 | 0 | 18179.2 | 18345.2 | 20457.9 | 573.7 | 582.3 | 73875.9 | 0.00 | 6.21 |
|
||||
| baseline | 0/11 | 0.77 | 2 | 24 | 3890.8 | 3646.2 | 5054.4 | 132.0 | 143.1 | 15318.6 | 0.00 | 1.01 |
|
||||
|
||||
## 相对基线的配对变化（虚拟时间）
|
||||
|
||||
| 配对 | 均值变化 | 中位变化 | 更快场景 | 双方均有效 |
|
||||
| --- | --- | --- | --- | --- |
|
||||
| optimal_vs_baseline | +142.9% | +141.4% | 0/11 | 0 |
|
||||
| baseline_grid_vs_baseline | +381.1% | +372.3% | 0/11 | 0 |
|
||||
|
||||
> 注：optimal_vs_baseline、baseline_grid_vs_baseline 存在未通过有效性判定的配对；其虚拟时间仅作参考，基线未完成全清任务时不构成「更快」证据（以「双方均有效」列为准）。
|
||||
@@ -0,0 +1,50 @@
|
||||
# 1-4 问最优 vs 基线：对比总览
|
||||
|
||||
本节所有数字由 `uv run python -m project.run` 在同机同口径下生成，
|
||||
逐问明细见 `q1.md` … `q4.md`。
|
||||
|
||||
| 问 | 核心指标 | 最优实现 | 基线实现 |
|
||||
| --- | --- | --- | --- |
|
||||
| 1 | 直径平均误差 / 覆盖准确率 | 0.00 m / 100% | 4.58 m / 52% |
|
||||
| 2 | 保证接收率 / 最坏后验均值 | 100% / 73.9 m | 100% / 340.7 m |
|
||||
| 3 | 全清率 / T 均值（相对基线） | 100% / 3189 s (-78%) | 100% / 14936 s |
|
||||
| 4 | 全清率 / 缺席误判（问题三策略搬用） | 100% / 0 | 77% / 24 |
|
||||
|
||||
## 方法映射
|
||||
|
||||
| 问 | 最优实现 | 基线实现 | 独立参考 |
|
||||
| --- | --- | --- | --- |
|
||||
| 1 | 半平面交 + 顶点对直径 + MEC | 网格采样 + bbox 对角线代理 | 大框半平面裁剪 + 精确直径/MEC |
|
||||
| 2 | 保证接收盘内最小最坏后验半径 | 垂直 1000 m / MEC 圆心 | 保证接收盘内网格枚举 |
|
||||
| 3 | bayes（粒子滤波 + 信息增益 + 滚动调度） | grid（49 点网格）/ seven（七点批量） | 冻结基准集 + 逐微秒计时复算 |
|
||||
| 4 | directional（联合信念 + 后备清除） | bayes / grid 直接搬用 | 冻结基准集 + 真值全清校验 |
|
||||
|
||||
## 目录结构
|
||||
|
||||
```text
|
||||
project/
|
||||
├── common.py 公共层：方法描述/指标聚合/结果落盘/闭环装配
|
||||
├── q1/ 问题一：直径与直径圆覆盖
|
||||
│ ├── optimal.py 生产实现：半平面交 + 顶点对直径 + MEC
|
||||
│ ├── baseline.py 基线：网格采样 + bbox 对角线代理
|
||||
│ ├── reference.py 参考：大框半平面裁剪 + 精确直径/MEC
|
||||
│ ├── cases.py 固定示例（examples/q1）+ 随机交会算例
|
||||
│ └── compare.py 同案配对对比
|
||||
├── q2/ 问题二：第二检测点选择
|
||||
│ ├── optimal.py 生产实现：保证接收盘内最小最坏后验半径
|
||||
│ ├── baseline.py 基线：垂直 1000 m / MEC 圆心
|
||||
│ ├── reference.py 参考：保证接收盘内网格枚举
|
||||
│ ├── region.py K1 统一构造
|
||||
│ ├── cases.py 随机首次示向度算例
|
||||
│ └── compare.py
|
||||
├── q3/ 问题三：全向闭环
|
||||
│ ├── optimal.py bayes（生产默认策略）
|
||||
│ ├── baseline.py grid（49 点网格）/ seven（七点批量）
|
||||
│ └── compare.py
|
||||
├── q4/ 问题四：混合源闭环
|
||||
│ ├── optimal.py directional（定向扩展）
|
||||
│ ├── baseline.py bayes / grid 直接搬用
|
||||
│ └── compare.py
|
||||
├── run.py 统一入口（本文件）
|
||||
└── results/ 自动生成：q1.md/json … q4.md/json + summary.md
|
||||
```
|
||||
Reference in New Issue
Block a user