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seq_arm_000_s0
arm
"a person raises both arms out to the sides and overhead -> the person lowers the arms and crosses t(...TRUNCATED)
train
human
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worldwide_civilian_2024
short
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seq_arm_000_s0
arm
"a person raises both arms out to the sides and overhead -> the person lowers the arms and crosses t(...TRUNCATED)
train
human
human_p50_median
worldwide_civilian_2024
median
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torso,head,shoulder_L,shoulder_R,arm_L,arm_R,hand_L,hand_R,leg_L,leg_R
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seq_arm_000_s0
arm
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human
human_p99_tall
worldwide_civilian_2024
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torso,head,shoulder_L,shoulder_R,arm_L,arm_R,hand_L,hand_R,leg_L,leg_R
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seq_arm_000_s1
arm
"a person raises both arms out to the sides and overhead -> the person lowers the arms and crosses t(...TRUNCATED)
train
human
human_p01_short
worldwide_civilian_2024
short
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180
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torso,head,shoulder_L,shoulder_R,arm_L,arm_R,hand_L,hand_R,leg_L,leg_R
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seq_arm_000_s1
arm
"a person raises both arms out to the sides and overhead -> the person lowers the arms and crosses t(...TRUNCATED)
train
human
human_p50_median
worldwide_civilian_2024
median
171.5
140
30
15
15
180
10
torso,head,shoulder_L,shoulder_R,arm_L,arm_R,hand_L,hand_R,leg_L,leg_R
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seq_arm_000_s1
arm
"a person raises both arms out to the sides and overhead -> the person lowers the arms and crosses t(...TRUNCATED)
train
human
human_p99_tall
worldwide_civilian_2024
tall
196
140
30
15
15
180
10
torso,head,shoulder_L,shoulder_R,arm_L,arm_R,hand_L,hand_R,leg_L,leg_R
[1.151926803956493,1.0816576388833408,1.2467874763498918,1.1714459729980558,1.1334232742026762,1.127(...TRUNCATED)
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seq_arm_000_s2
arm
"a person raises both arms out to the sides and overhead -> the person lowers the arms and crosses t(...TRUNCATED)
train
human
human_p01_short
worldwide_civilian_2024
short
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140
30
15
15
180
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torso,head,shoulder_L,shoulder_R,arm_L,arm_R,hand_L,hand_R,leg_L,leg_R
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177.452957
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seq_arm_000_s2
arm
"a person raises both arms out to the sides and overhead -> the person lowers the arms and crosses t(...TRUNCATED)
train
human
human_p50_median
worldwide_civilian_2024
median
171.5
140
30
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15
180
10
torso,head,shoulder_L,shoulder_R,arm_L,arm_R,hand_L,hand_R,leg_L,leg_R
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seq_arm_000_s2
arm
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train
human
human_p99_tall
worldwide_civilian_2024
tall
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15
15
180
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torso,head,shoulder_L,shoulder_R,arm_L,arm_R,hand_L,hand_R,leg_L,leg_R
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seq_arm_000_s7
arm
"a person raises both arms out to the sides and overhead -> the person lowers the arms and crosses t(...TRUNCATED)
train
human
human_p01_short
worldwide_civilian_2024
short
140
140
30
15
15
180
10
torso,head,shoulder_L,shoulder_R,arm_L,arm_R,hand_L,hand_R,leg_L,leg_R
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178.424667
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End of preview. Expand in Data Studio

mount-drift-caldata-motion

Generated continuous motions with constructed inertial-suit calibration data, for training a tracker mount-drift calibrator.

What it is for

A mount-drift calibrator recovers, from a worn inertial suit's raw per-sensor stream, the constant sensor-to-bone mount rotations and the shared world heading drift. Each row holds one whole continuous SOMA30 motion clip rendered onto one body phenotype, with the calibration input caldata_x and the targets caldata_y and phenotype_fit_target. The motions excite the arm and hand degrees of freedom, because gait and standing data starve the signal that identifies arm and hand mounts. Two configs cover two body populations: human and starforged. Both are bounded to the same stature envelope. Splits are assigned per clip, so a motion and all its phenotype re-renders stay in one split. Every clip passes a validity gate for non-finite values, degenerate quaternions, joint range and teleports. microduck_qa.json records the gate result for every generated clip, including rejections. The set is not a sole training distribution for a deployed calibrator. It mixes with real inertial captures.

Provenance

  • Motion is generated synthetic, sampled from the Kimodo text-to-motion diffusion model kimodo-soma-rp-v1.1 (SOMA30 skeleton, DDIM 16 steps, text-cfg 2.5). Each row records its prompt chain.
  • Calibration data is constructed synthetic. Each sensor reports M = D · C · R, where D is a world heading drift, C the clean bone orientation and R the sensor mount. Labels are exact and the same seed reproduces them.
  • Body anthropometry comes from chibifire/starforged-std-3001-appendix-e.
  • The validity gate is modeled on pollen-robotics/microduck's safety.rs.
  • Citation metadata is in CITATION.cff.

Use

from datasets import load_dataset
human      = load_dataset("chibifire/mount-drift-caldata-motion", "human")
starforged = load_dataset("chibifire/mount-drift-caldata-motion", "starforged")

Licence

CC-BY-4.0.

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