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120 values
frame_no
int64
1
2.08k
ts_pcd
float64
1.78B
1.79B
seg_reached
int64
-1
1
frame_recovered
int64
-1
1
dlo_n001_x
float64
0.36
0.56
โŒ€
dlo_n001_y
float64
1.43
1.6
โŒ€
dlo_n001_z
float64
0.48
0.76
โŒ€
dlo_n002_x
float64
0.35
0.56
โŒ€
dlo_n002_y
float64
1.43
1.6
โŒ€
dlo_n002_z
float64
0.47
0.76
โŒ€
dlo_n003_x
float64
0.35
0.56
โŒ€
dlo_n003_y
float64
1.42
1.59
โŒ€
dlo_n003_z
float64
0.47
0.77
โŒ€
dlo_n004_x
float64
0.35
0.57
โŒ€
dlo_n004_y
float64
1.41
1.6
โŒ€
dlo_n004_z
float64
0.46
0.77
โŒ€
dlo_n005_x
float64
0.35
0.57
โŒ€
dlo_n005_y
float64
1.41
1.6
โŒ€
dlo_n005_z
float64
0.45
0.77
โŒ€
dlo_n006_x
float64
0.35
0.57
โŒ€
dlo_n006_y
float64
1.4
1.61
โŒ€
dlo_n006_z
float64
0.44
0.77
โŒ€
dlo_n007_x
float64
0.35
0.58
โŒ€
dlo_n007_y
float64
1.39
1.61
โŒ€
dlo_n007_z
float64
0.43
0.78
โŒ€
dlo_n008_x
float64
0.35
0.58
โŒ€
dlo_n008_y
float64
1.38
1.61
โŒ€
dlo_n008_z
float64
0.42
0.78
โŒ€
dlo_n009_x
float64
0.35
0.58
โŒ€
dlo_n009_y
float64
1.38
1.61
โŒ€
dlo_n009_z
float64
0.41
0.78
โŒ€
dlo_n010_x
float64
0.34
0.58
โŒ€
dlo_n010_y
float64
1.37
1.62
โŒ€
dlo_n010_z
float64
0.4
0.77
โŒ€
dlo_n011_x
float64
0.34
0.58
โŒ€
dlo_n011_y
float64
1.36
1.62
โŒ€
dlo_n011_z
float64
0.4
0.77
โŒ€
dlo_n012_x
float64
0.33
0.59
โŒ€
dlo_n012_y
float64
1.36
1.62
โŒ€
dlo_n012_z
float64
0.39
0.77
โŒ€
dlo_n013_x
float64
0.33
0.61
โŒ€
dlo_n013_y
float64
1.35
1.62
โŒ€
dlo_n013_z
float64
0.38
0.77
โŒ€
dlo_n014_x
float64
0.32
0.63
โŒ€
dlo_n014_y
float64
1.34
1.62
โŒ€
dlo_n014_z
float64
0.38
0.76
โŒ€
dlo_n015_x
float64
0.32
0.65
โŒ€
dlo_n015_y
float64
1.34
1.63
โŒ€
dlo_n015_z
float64
0.37
0.76
โŒ€
dlo_n016_x
float64
0.31
0.67
โŒ€
dlo_n016_y
float64
1.33
1.63
โŒ€
dlo_n016_z
float64
0.37
0.76
โŒ€
dlo_n017_x
float64
0.31
0.69
โŒ€
dlo_n017_y
float64
1.33
1.63
โŒ€
dlo_n017_z
float64
0.36
0.76
โŒ€
dlo_n018_x
float64
0.3
0.71
โŒ€
dlo_n018_y
float64
1.32
1.63
โŒ€
dlo_n018_z
float64
0.36
0.76
โŒ€
dlo_n019_x
float64
0.29
0.73
โŒ€
dlo_n019_y
float64
1.31
1.63
โŒ€
dlo_n019_z
float64
0.36
0.76
โŒ€
dlo_n020_x
float64
0.29
0.75
โŒ€
dlo_n020_y
float64
1.31
1.63
โŒ€
dlo_n020_z
float64
0.35
0.76
โŒ€
dlo_n021_x
float64
0.28
0.77
โŒ€
dlo_n021_y
float64
1.3
1.63
โŒ€
dlo_n021_z
float64
0.36
0.76
โŒ€
dlo_n022_x
float64
0.28
0.78
โŒ€
dlo_n022_y
float64
1.29
1.63
โŒ€
dlo_n022_z
float64
0.36
0.76
โŒ€
dlo_n023_x
float64
0.27
0.77
โŒ€
dlo_n023_y
float64
1.29
1.63
โŒ€
dlo_n023_z
float64
0.37
0.76
โŒ€
dlo_n024_x
float64
0.26
0.76
โŒ€
dlo_n024_y
float64
1.28
1.64
โŒ€
dlo_n024_z
float64
0.36
0.76
โŒ€
dlo_n025_x
float64
0.25
0.74
โŒ€
dlo_n025_y
float64
1.27
1.64
โŒ€
dlo_n025_z
float64
0.35
0.76
โŒ€
dlo_n026_x
float64
0.24
0.72
โŒ€
dlo_n026_y
float64
1.26
1.64
โŒ€
dlo_n026_z
float64
0.34
0.76
โŒ€
dlo_n027_x
float64
0.23
0.7
โŒ€
dlo_n027_y
float64
1.26
1.64
โŒ€
dlo_n027_z
float64
0.33
0.76
โŒ€
dlo_n028_x
float64
0.23
0.68
โŒ€
dlo_n028_y
float64
1.25
1.64
โŒ€
dlo_n028_z
float64
0.33
0.76
โŒ€
dlo_n029_x
float64
0.22
0.67
โŒ€
dlo_n029_y
float64
1.24
1.64
โŒ€
dlo_n029_z
float64
0.32
0.76
โŒ€
dlo_n030_x
float64
0.21
0.65
โŒ€
dlo_n030_y
float64
1.23
1.64
โŒ€
dlo_n030_z
float64
0.32
0.76
โŒ€
dlo_n031_x
float64
0.21
0.66
โŒ€
dlo_n031_y
float64
1.22
1.64
โŒ€
dlo_n031_z
float64
0.33
0.76
โŒ€
dlo_n032_x
float64
0.21
0.66
โŒ€
dlo_n032_y
float64
1.21
1.64
โŒ€
dlo_n032_z
float64
0.32
0.76
โŒ€
dlo_n033_x
float64
0.2
0.67
โŒ€
dlo_n033_y
float64
1.21
1.64
โŒ€
dlo_n033_z
float64
0.32
0.76
โŒ€
dlo_n034_x
float64
0.2
0.67
โŒ€
dlo_n034_y
float64
1.2
1.64
โŒ€
dlo_n034_z
float64
0.32
0.76
โŒ€
dlo_n035_x
float64
0.19
0.68
โŒ€
dlo_n035_y
float64
1.2
1.64
โŒ€
dlo_n035_z
float64
0.32
0.76
โŒ€
dlo_n036_x
float64
0.19
0.68
โŒ€
dlo_n036_y
float64
1.2
1.65
โŒ€
dlo_n036_z
float64
0.31
0.76
โŒ€
dlo_n037_x
float64
0.18
0.68
โŒ€
dlo_n037_y
float64
1.2
1.65
โŒ€
dlo_n037_z
float64
0.3
0.76
โŒ€
dlo_n038_x
float64
0.18
0.69
โŒ€
dlo_n038_y
float64
1.2
1.65
โŒ€
dlo_n038_z
float64
0.3
0.76
โŒ€
dlo_n039_x
float64
0.17
0.69
โŒ€
dlo_n039_y
float64
1.2
1.65
โŒ€
dlo_n039_z
float64
0.29
0.76
โŒ€
dlo_n040_x
float64
0.17
0.7
โŒ€
dlo_n040_y
float64
1.2
1.65
โŒ€
dlo_n040_z
float64
0.29
0.76
โŒ€
dlo_n041_x
float64
0.17
0.7
โŒ€
dlo_n041_y
float64
1.19
1.65
โŒ€
dlo_n041_z
float64
0.28
0.76
โŒ€
dlo_n042_x
float64
0.16
0.71
โŒ€
dlo_n042_y
float64
1.18
1.65
โŒ€
dlo_n042_z
float64
0.27
0.76
โŒ€
dlo_n043_x
float64
0.16
0.71
โŒ€
dlo_n043_y
float64
1.17
1.64
โŒ€
dlo_n043_z
float64
0.27
0.76
โŒ€
dlo_n044_x
float64
0.15
0.71
โŒ€
dlo_n044_y
float64
1.16
1.64
โŒ€
dlo_n044_z
float64
0.26
0.76
โŒ€
dlo_n045_x
float64
0.15
0.72
โŒ€
dlo_n045_y
float64
1.16
1.64
โŒ€
dlo_n045_z
float64
0.25
0.76
โŒ€
dlo_n046_x
float64
0.15
0.72
โŒ€
dlo_n046_y
float64
1.15
1.64
โŒ€
dlo_n046_z
float64
0.25
0.76
โŒ€
dlo_n047_x
float64
0.14
0.73
โŒ€
dlo_n047_y
float64
1.15
1.63
โŒ€
dlo_n047_z
float64
0.24
0.76
โŒ€
dlo_n048_x
float64
0.14
0.73
โŒ€
dlo_n048_y
float64
1.15
1.63
โŒ€
dlo_n048_z
float64
0.23
0.76
โŒ€
dlo_n049_x
float64
0.14
0.73
โŒ€
dlo_n049_y
float64
1.14
1.63
โŒ€
dlo_n049_z
float64
0.23
0.76
โŒ€
dlo_n050_x
float64
0.14
0.74
โŒ€
dlo_n050_y
float64
1.13
1.63
โŒ€
dlo_n050_z
float64
0.22
0.77
โŒ€
dlo_n051_x
float64
0.14
0.74
โŒ€
dlo_n051_y
float64
1.13
1.63
โŒ€
dlo_n051_z
float64
0.21
0.77
โŒ€
dlo_n052_x
float64
0.13
0.74
โŒ€
dlo_n052_y
float64
1.12
1.63
โŒ€
dlo_n052_z
float64
0.21
0.78
โŒ€
dlo_n053_x
float64
0.13
0.75
โŒ€
dlo_n053_y
float64
1.11
1.63
โŒ€
dlo_n053_z
float64
0.2
0.79
โŒ€
dlo_n054_x
float64
0.13
0.75
โŒ€
dlo_n054_y
float64
1.11
1.63
โŒ€
dlo_n054_z
float64
0.2
0.79
โŒ€
dlo_n055_x
float64
0.13
0.75
โŒ€
dlo_n055_y
float64
1.1
1.64
โŒ€
dlo_n055_z
float64
0.19
0.8
โŒ€
dlo_n056_x
float64
0.13
0.76
โŒ€
dlo_n056_y
float64
1.09
1.64
โŒ€
dlo_n056_z
float64
0.19
0.8
โŒ€
dlo_n057_x
float64
0.13
0.76
โŒ€
dlo_n057_y
float64
1.09
1.64
โŒ€
dlo_n057_z
float64
0.18
0.81
โŒ€
dlo_n058_x
float64
0.12
0.76
โŒ€
dlo_n058_y
float64
1.08
1.65
โŒ€
dlo_n058_z
float64
0.18
0.82
โŒ€
dlo_n059_x
float64
0.12
0.77
โŒ€
dlo_n059_y
float64
1.08
1.65
โŒ€
dlo_n059_z
float64
0.17
0.82
โŒ€
dlo_n060_x
float64
0.12
0.77
โŒ€
dlo_n060_y
float64
1.07
1.66
โŒ€
dlo_n060_z
float64
0.17
0.83
โŒ€
dlo_n061_x
float64
0.12
0.77
โŒ€
dlo_n061_y
float64
1.06
1.66
โŒ€
dlo_n061_z
float64
0.17
0.84
โŒ€
dlo_n062_x
float64
0.12
0.78
โŒ€
dlo_n062_y
float64
1.06
1.67
โŒ€
dlo_n062_z
float64
0.16
0.84
โŒ€
dlo_n063_x
float64
0.11
0.78
โŒ€
dlo_n063_y
float64
1.05
1.67
โŒ€
dlo_n063_z
float64
0.16
0.85
โŒ€
dlo_n064_x
float64
0.11
0.78
โŒ€
dlo_n064_y
float64
1.05
1.66
โŒ€
dlo_n064_z
float64
0.16
0.86
โŒ€
dlo_n065_x
float64
0.1
0.79
โŒ€
dlo_n065_y
float64
1.04
1.66
โŒ€
dlo_n065_z
float64
0.15
0.86
โŒ€
dlo_n066_x
float64
0.1
0.79
โŒ€
dlo_n066_y
float64
1.03
1.65
โŒ€
dlo_n066_z
float64
0.15
0.87
โŒ€
dlo_n067_x
float64
0.09
0.8
โŒ€
dlo_n067_y
float64
1.03
1.65
โŒ€
dlo_n067_z
float64
0.14
0.88
โŒ€
dlo_n068_x
float64
0.09
0.8
โŒ€
dlo_n068_y
float64
1.02
1.64
โŒ€
dlo_n068_z
float64
0.14
0.88
โŒ€
dlo_n069_x
float64
0.08
0.81
โŒ€
dlo_n069_y
float64
1.01
1.64
โŒ€
dlo_n069_z
float64
0.13
0.89
โŒ€
dlo_n070_x
float64
0.08
0.81
โŒ€
dlo_n070_y
float64
1.01
1.63
โŒ€
dlo_n070_z
float64
0.13
0.9
โŒ€
dlo_n071_x
float64
0.07
0.81
โŒ€
dlo_n071_y
float64
1
1.62
โŒ€
dlo_n071_z
float64
0.13
0.9
โŒ€
dlo_n072_x
float64
0.07
0.82
โŒ€
dlo_n072_y
float64
1
1.62
โŒ€
dlo_n072_z
float64
0.12
0.91
โŒ€
dlo_n073_x
float64
0.06
0.82
โŒ€
dlo_n073_y
float64
0.99
1.61
โŒ€
dlo_n073_z
float64
0.12
0.92
โŒ€
dlo_n074_x
float64
0.06
0.83
โŒ€
dlo_n074_y
float64
0.98
1.6
โŒ€
dlo_n074_z
float64
0.12
0.92
โŒ€
dlo_n075_x
float64
0.06
0.83
โŒ€
dlo_n075_y
float64
0.98
1.59
โŒ€
dlo_n075_z
float64
0.11
0.93
โŒ€
dlo_n076_x
float64
0.05
0.83
โŒ€
dlo_n076_y
float64
0.97
1.59
โŒ€
dlo_n076_z
float64
0.1
0.94
โŒ€
dlo_n077_x
float64
0.05
0.84
โŒ€
dlo_n077_y
float64
0.96
1.58
โŒ€
dlo_n077_z
float64
0.1
0.94
โŒ€
dlo_n078_x
float64
0.04
0.84
โŒ€
dlo_n078_y
float64
0.96
1.57
โŒ€
dlo_n078_z
float64
0.09
0.95
โŒ€
dlo_n079_x
float64
0.04
0.85
โŒ€
dlo_n079_y
float64
0.95
1.56
โŒ€
dlo_n079_z
float64
0.09
0.96
โŒ€
dlo_n080_x
float64
0.04
0.85
โŒ€
dlo_n080_y
float64
0.94
1.56
โŒ€
dlo_n080_z
float64
0.08
0.96
โŒ€
dlo_n081_x
float64
0.04
0.86
โŒ€
dlo_n081_y
float64
0.94
1.55
โŒ€
dlo_n081_z
float64
0.08
0.97
โŒ€
dlo_n082_x
float64
0.03
0.86
โŒ€
dlo_n082_y
float64
0.93
1.54
โŒ€
dlo_n082_z
float64
0.07
0.97
โŒ€
dlo_n083_x
float64
0.03
0.87
โŒ€
dlo_n083_y
float64
0.92
1.54
โŒ€
dlo_n083_z
float64
0.07
0.98
โŒ€
dlo_n084_x
float64
0.03
0.87
โŒ€
dlo_n084_y
float64
0.92
1.53
โŒ€
dlo_n084_z
float64
0.07
0.98
โŒ€
dlo_n085_x
float64
0.03
0.87
โŒ€
dlo_n085_y
float64
0.91
1.52
โŒ€
dlo_n085_z
float64
0.06
0.98
โŒ€
dlo_n086_x
float64
0.03
0.88
โŒ€
dlo_n086_y
float64
0.9
1.51
โŒ€
dlo_n086_z
float64
0.06
0.99
โŒ€
dlo_n087_x
float64
0.03
0.88
โŒ€
dlo_n087_y
float64
0.9
1.51
โŒ€
dlo_n087_z
float64
0.06
0.99
โŒ€
dlo_n088_x
float64
0.03
0.89
โŒ€
dlo_n088_y
float64
0.89
1.5
โŒ€
dlo_n088_z
float64
0.06
0.99
โŒ€
dlo_n089_x
float64
0.03
0.89
โŒ€
dlo_n089_y
float64
0.88
1.49
โŒ€
dlo_n089_z
float64
0.06
1
โŒ€
dlo_n090_x
float64
0.03
0.89
โŒ€
dlo_n090_y
float64
0.88
1.49
โŒ€
dlo_n090_z
float64
0.06
1
โŒ€
dlo_n091_x
float64
0.03
0.9
โŒ€
dlo_n091_y
float64
0.87
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โŒ€
dlo_n091_z
float64
0.06
1
โŒ€
dlo_n092_x
float64
0.03
0.9
โŒ€
dlo_n092_y
float64
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โŒ€
dlo_n092_z
float64
0.06
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โŒ€
dlo_n093_x
float64
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0.91
โŒ€
dlo_n093_y
float64
0.86
1.47
โŒ€
dlo_n093_z
float64
0.06
0.99
โŒ€
dlo_n094_x
float64
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0.91
โŒ€
dlo_n094_y
float64
0.85
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โŒ€
dlo_n094_z
float64
0.06
0.99
โŒ€
dlo_n095_x
float64
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0.91
โŒ€
dlo_n095_y
float64
0.84
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โŒ€
dlo_n095_z
float64
0.06
0.99
โŒ€
dlo_n096_x
float64
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0.9
โŒ€
dlo_n096_y
float64
0.84
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โŒ€
dlo_n096_z
float64
0.06
0.99
โŒ€
dlo_n097_x
float64
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0.9
โŒ€
dlo_n097_y
float64
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โŒ€
dlo_n097_z
float64
0.06
0.98
โŒ€
dlo_n098_x
float64
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0.9
โŒ€
dlo_n098_y
float64
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1.44
โŒ€
dlo_n098_z
float64
0.06
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โŒ€
dlo_n099_x
float64
0.04
0.89
โŒ€
dlo_n099_y
float64
0.82
1.43
โŒ€
dlo_n099_z
float64
0.06
0.98
โŒ€
dlo_n100_x
float64
0.04
0.89
โŒ€
dlo_n100_y
float64
0.81
1.42
โŒ€
dlo_n100_z
float64
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โŒ€
t001_d001_v050
1
1,783,630,315.990058
1
-1
0.529299
1.517077
0.520883
0.528727
1.510674
0.521973
0.527667
1.504247
0.52226
0.526181
1.497922
0.5217
0.524374
1.491811
0.520318
0.522367
1.485978
0.518198
0.520273
1.480449
0.515442
0.518184
1.475211
0.51216
0.516174
1.470236
0.508448
0.514294
1.465487
0.504387
0.512582
1.460926
0.500045
0.511067
1.456517
0.495479
0.509765
1.452227
0.490738
0.508687
1.448024
0.485863
0.507837
1.443883
0.480892
0.507212
1.439778
0.475857
0.506806
1.435688
0.470788
0.506607
1.431593
0.465711
0.506599
1.427476
0.460648
0.506763
1.423319
0.455619
0.507076
1.419108
0.450643
0.507513
1.414831
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0.50805
1.410474
0.440904
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1.406028
0.436166
0.50931
1.401484
0.431528
0.509979
1.396833
0.426999
0.510641
1.392071
0.422586
0.511272
1.387193
0.418297
0.51185
1.382196
0.414139
0.512359
1.37708
0.410119
0.512771
1.371848
0.406242
0.513052
1.366508
0.402501
0.513322
1.361062
0.398915
0.513565
1.355509
0.395494
0.513775
1.349848
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0.51411
1.338194
0.386394
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1.3322
0.383818
0.514359
1.326097
0.38151
0.514442
1.31989
0.379496
0.514469
1.31359
0.377796
0.514404
1.307216
0.376398
0.514311
1.300784
0.375306
0.514206
1.294305
0.374532
0.514096
1.287796
0.37408
0.513985
1.281273
0.373953
0.513877
1.274751
0.374149
0.513773
1.268246
0.374664
0.513676
1.261774
0.375491
0.513584
1.255348
0.376623
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1.248981
0.378048
0.513416
1.242683
0.379756
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0.513259
1.230334
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1.224297
0.386446
0.513092
1.218361
0.389156
0.512999
1.21253
0.392085
0.512896
1.206808
0.39522
0.51278
1.201198
0.398552
0.512649
1.195702
0.40207
0.512501
1.190325
0.405764
0.512235
1.185101
0.409664
0.512034
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0.4138
0.511975
1.175138
0.418087
0.512016
1.170303
0.422471
0.512122
1.165529
0.42692
0.512261
1.160807
0.431422
0.512407
1.156137
0.435979
0.512535
1.151532
0.440602
0.512623
1.147009
0.445305
0.51265
1.142587
0.450105
0.512395
1.138393
0.455095
0.51201
1.134416
0.460254
0.51157
1.130622
0.465546
0.511087
1.126996
0.47095
0.51057
1.123511
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0.510027
1.120137
0.482004
0.509462
1.116839
0.487607
0.508881
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0.493231
0.508286
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0.507676
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0.506414
1.100104
0.515447
0.505756
1.09642
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1.092528
0.525987
0.504369
1.088397
0.530989
0.503628
1.083997
0.535751
0.502848
1.079312
0.540224
0.50202
1.074333
0.54436
0.501138
1.069069
0.548112
0.500192
1.063539
0.551443
0.499175
1.057774
0.554324
0.498077
1.051814
0.556742
0.496887
1.045703
0.558695
0.495594
1.039485
0.560189
0.494182
1.033202
0.561241
0.492633
1.026895
0.561869
0.490924
1.020602
0.562094
0.48902
1.014363
0.561931
0.48688
1.008222
0.561398
t001_d001_v050
2
1,783,630,316.030267
1
-1
0.530185
1.515549
0.521072
0.531379
1.509148
0.522021
0.531578
1.502576
0.522233
0.530775
1.496079
0.521593
0.529139
1.489878
0.520117
0.526933
1.48408
0.51791
0.524404
1.478686
0.515102
0.521749
1.473642
0.511801
0.51911
1.468879
0.508094
0.516593
1.464332
0.504045
0.514277
1.459946
0.499708
0.512222
1.455677
0.49513
0.510471
1.451487
0.490357
0.50905
1.447347
0.485433
0.507972
1.443235
0.4804
0.50723
1.439131
0.475299
0.506807
1.435019
0.470169
0.506673
1.430886
0.465039
0.506789
1.426719
0.459937
0.507111
1.422504
0.454883
0.50759
1.418231
0.44989
0.508179
1.413887
0.444971
0.508829
1.409462
0.440133
0.509494
1.404945
0.435382
0.510131
1.400328
0.430724
0.510702
1.395604
0.426166
0.511174
1.390769
0.421715
0.511524
1.385821
0.417379
0.511739
1.380758
0.413167
0.511816
1.375583
0.40909
0.511881
1.370304
0.405149
0.512114
1.364915
0.401364
0.51244
1.359416
0.39775
0.512811
1.3538
0.394324
0.5132
1.348065
0.391104
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1.342208
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1.336228
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1.323916
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1.317602
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1.311211
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1.304749
0.375999
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0.375044
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0.515369
1.24598
0.378607
0.515614
1.239643
0.380395
0.515788
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0.51587
1.22723
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1.221176
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1.215237
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0.51281
1.187597
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1.139731
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1.110243
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1.075297
0.543328
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1.07025
0.547203
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1.064943
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1.059402
0.553576
0.499114
1.053662
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0.497022
1.047754
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0.494966
1.041706
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1.035537
0.560921
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1.029264
0.561814
0.489627
1.022895
0.562421
0.488367
1.01644
0.562795
0.487535
1.009908
0.562993
0.487287
1.003327
0.56309
t001_d001_v050
3
1,783,630,316.070476
1
-1
0.528337
1.51622
0.520844
0.527118
1.509896
0.521874
0.525733
1.503527
0.522084
0.524227
1.497217
0.521428
0.522656
1.491069
0.519922
0.521082
1.485163
0.517646
0.519559
1.479538
0.514716
0.518125
1.474198
0.511253
0.516807
1.469123
0.507369
0.515621
1.464282
0.503159
0.514573
1.459637
0.498696
0.513668
1.455151
0.494044
0.512906
1.45079
0.48925
0.512282
1.446523
0.484353
0.511795
1.44232
0.479385
0.511436
1.438156
0.474372
0.5112
1.43401
0.469338
0.511078
1.42986
0.464303
0.511061
1.425691
0.459283
0.511138
1.421485
0.454294
0.5113
1.417229
0.449349
0.511533
1.412911
0.444461
0.511825
1.408521
0.439642
0.512163
1.404049
0.434901
0.512534
1.399487
0.430249
0.512925
1.394831
0.425694
0.513324
1.390073
0.421246
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1.385209
0.416913
0.514099
1.380235
0.412705
0.514454
1.375149
0.408631
0.514726
1.369945
0.404704
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1.364621
0.400937
0.515228
1.359177
0.397349
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1.35361
0.393958
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1.347918
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1.013333
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1.007161
0.561962
t001_d001_v050
4
1,783,630,316.110684
1
-1
0.528432
1.517541
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1.510987
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t001_d001_v050
5
1,783,630,316.150893
1
-1
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t001_d001_v050
6
1,783,630,316.191101
1
-1
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t001_d001_v050
7
1,783,630,316.231309
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-1
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t001_d001_v050
8
1,783,630,316.271518
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t001_d001_v050
9
1,783,630,316.311726
1
-1
0.528603
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t001_d001_v050
10
1,783,630,316.351935
1
-1
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1.517976
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t001_d001_v050
11
1,783,630,316.392142
1
-1
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t001_d001_v050
12
1,783,630,316.432351
1
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t001_d001_v050
13
1,783,630,316.47256
1
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t001_d001_v050
14
1,783,630,316.512769
1
-1
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t001_d001_v050
15
1,783,630,316.552977
1
-1
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t001_d001_v050
16
1,783,630,316.593185
1
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t001_d001_v050
17
1,783,630,316.633393
1
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1.109459
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0.508313
1.106078
0.505065
0.508399
1.102626
0.51063
0.508402
1.099063
0.516125
0.508283
1.095348
0.521518
0.508002
1.091444
0.526769
0.507522
1.087317
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0.506811
1.082939
0.536647
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1.078292
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1.073376
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0.487946
1.020731
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t001_d001_v050
18
1,783,630,316.673602
1
-1
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1.434291
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1.43017
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1.426032
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1.413339
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1.404485
0.43496
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1.399901
0.430306
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End of preview. Expand in Data Studio

UPD-DLO: Unified Perception and Dynamics Benchmark for Deformable Linear Objects (10% Release)

UPD-DLO pairs real-world point clouds of deformable linear objects (DLOs) with frame-by-frame ground-truth centerlines and the robot motion that drives them, for benchmarking DLO perception (shape tracking) and dynamics (shape prediction) on the same episodes.

This repository holds the 10% release that accompanies the paper under review: tests t001-t010 of every batch, 120 of the 1,200 recorded episodes. The full dataset follows on acceptance.

At a Glance

Item Value
Objects 4: d001 black nylon rope, d002 white power cord, d003 tan manila rope, d004 blue cat5e cable bundle (3x)
Speeds 3 trajectory speeds: v050, v070, v100
Batches 12 (object x speed), 10 episodes each in this release
Episodes 120 (t001-t010 per batch)
Frames 114,130 ground-truth frames, 510-2,083 per episode (median 886)
Frame rate about 20 Hz point clouds (median frame interval 0.050 s); joint states per message
Sensors statically mounted Intel RealSense L515 (point cloud, RGB); robot joint states and end-point state
Robot Baxter, left arm; the DLO hangs between a fixed pole and the gripper
Ground truth 100-point centerline per frame, equal arc length, robot frame, metres

Versions

Item Version
Release upd-dlo_ds001 pr001_p010
Code release rv001
Ground truth v044 (stored in _out_v044/ folders)
Perception evaluation prc011
Dynamics evaluation dyn009
Training trn001
Evaluation run eval009

Repository Layout

Path Content Files Size
LICENSE-DATA data license 1 20.9 KB
bags/ collected-episode list 1 0.3 KB
calib/ camera-to-robot calibrations 80 0.8 MB
eval/ fit/hold-out split per batch (as in the paper) 12 4.4 KB
groundtruth/<batch>/<ep>.tar GT v044 per episode 120 5.0 GB
objects/ object table 1 2.1 KB
parquet/ spline and frame-log tables (viewer) 24 0.7 GB
raw_data/<batch>/<ep>.tar camera and robot data per episode 120 262.9 GB
trajectories/ arm trajectories per test 165 75.3 MB
groundtruth/<batch>/<episode>.tar   -> groundtruth/<batch>/<episode>/_out_v044/...
raw_data/<batch>/<episode>.tar      -> raw_data/<batch>/<episode>/...
bags/bags_collected.txt             released episodes per batch
eval/<batch>/_batch/split.json      fit and hold-out episodes per batch
calib/  objects/  trajectories/     calibration, object table, arm trajectories
parquet/                            ground-truth tables for the dataset viewer

Quick Start

git lfs install
git clone <this repository>
cd <repository>
sha256sum -c MANIFEST.sha256
for t in groundtruth/*/*.tar raw_data/*/*.tar; do tar -xf "$t"; done

Each tar unpacks in place, so the unpacked tree matches the layout the code release reads. The code release (rv001) expects this tree at ~/bags/test_session_001/. manifest_members.tsv.gz lists every file inside the tars with its size and sha256.

Files per Episode

Ground truth, groundtruth/<batch>/<episode>/_out_v044/:

File Content
dlo_spline_n100.csv ground-truth centerline per frame: 100 points at equal arc length (x, y, z in metres, robot frame)
run_frame_log.csv per-frame log: status, point counts, gripper and pole poses, timing
run_frame_log_interpolated.csv the frame log with failed frames interpolated
episode_stats.json, episode_health.json frame counts, pass rate, initial DLO length
episode_summary.log per-episode summary; the code release treats it as the "ground truth finished" marker
calib_check.json, init_pose_check.json calibration and initial-pose checks
dlo_raw_crop_pcd/ cropped DLO point cloud per frame (input of the perception benchmark)
dlo_nodes_pcd/ ground-truth nodes per frame
eps_data/ gripper and pole poses, crop boxes, timestamps, pipeline configuration

Raw data, raw_data/<batch>/<episode>/:

File Content
pcd/ camera point cloud per frame
rgb/ color image per frame
jointstate/, left_endpoint/ robot joint state and left end-point state per message
timestamp_fix.json color-image timestamp correction

The first line of each CSV is a # comment (file, episode, ground-truth version); read it with comment="#" or skip one line. Frame files are named <frame>_seq-<n>_sec-<s>_nsec-<ns>_rostime-<t>.

Benchmark Split

eval/<batch>/_batch/split.json holds the split used in the paper: per batch 8 fit episodes and 2 hold-out episodes (t002, t010). Models are fit on the fit episodes; every reported metric is computed on the hold-out episodes only.

License

The data is licensed under CC BY-NC-SA 4.0 (LICENSE-DATA).

Citation

Withheld for double-anonymous review; it will be added on acceptance.

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