license: apache-2.0
task_categories:
- robotics
tags:
- humanoid
- motion-tracking
- locomotion
- ff-master
- phc
viewer: false
motionSample — FF Master motion references
Joint-space motion references for the FF Master humanoid (31 DoF), stored in the PHC-style pickle format used by the humanoid motion-tracking codebase family (PHC / H2O / OmniH2O / ASAP / HumanoidVerse).
Interactive viewer: Master Motion Sample Space
| Clips | 2 (one file each) |
| Frames | 2759 total |
| FPS | 120 (inferred — see below) |
| DoF | 31 |
| Robot | FF Master (URDF x2_ultra) |
One file per clip — they are not bundled together. highjump is trimmed to 5 consecutive
jumps (source frames 654–1589 of a 21-jump take); jogging is the full take.
| file | clip key | frames | duration | size |
|---|---|---|---|---|
jogging.pkl |
jogging |
1824 | 15.2 s | 1.3 MB |
highjump.pkl |
highjump |
935 | 7.8 s | 0.7 MB |
Loading
Each file holds a {clip_name: {...}} dict with a single entry, so PHC-family loaders that
expect a dict-of-motions read a single file without any code change.
import pickle
d = pickle.load(open("highjump.pkl", "rb"))
list(d) # ['highjump']
m = d["highjump"]
m["dof"].shape # (935, 31) joint angles, rad
m["root_trans_offset"].shape # (935, 3) base position, m
m["root_rot"].shape # (935, 4) base orientation, xyzw
m["fps"] # 120
To use both at once, merge them:
import glob, pickle
d = {}
for f in sorted(glob.glob("*.pkl")):
d.update(pickle.load(open(f, "rb")))
list(d) # ['highjump', 'jogging']
Keys
Key names are the union of what the PHC family reads. Each framework picks up the subset it knows; the extras are inert.
| key | shape | read by |
|---|---|---|
root_trans_offset |
(T, 3) | all |
root_rot |
(T, 4) xyzw | all |
pose_aa |
(T, 1+31, 3) | PHC / H2O / OmniH2O |
dof |
(T, 31) | all |
fps |
int = 120 | all |
dof_pos |
(T, 31), same array as dof |
ASAP / HumanoidVerse |
dof_vel |
(T, 31) | ASAP / HumanoidVerse |
root_lin_vel / root_ang_vel |
(T, 3) | ASAP / HumanoidVerse |
contacts |
(T, 2) left / right foot | — |
com_pos |
(T, 3) whole-body centre of mass, world frame | — |
total_mass |
float = 42.0 kg (from the URDF) | — |
dof_names / body_names |
list | — |
dof_axes |
(31, 3) | — |
quat_order |
"xyzw" |
— |
pose_aa
Per-body local rotation in axis-angle form, root first. For a 1-DoF revolute joint the
local rotation is a turn of q about the URDF axis, so the axis-angle vector is just
axis * q:
pose_aa[t, 0] = axis-angle of root_rot
pose_aa[t, 1 + j] = dof_axes[j] * dof[t, j]
dof_axes ships with the file, so pose_aa can be rebuilt or cross-checked without the URDF.
Conventions
- Quaternions are xyzw (PHC / Isaac). MuJoCo and USD use wxyz — reorder when crossing over.
- z up, soles at z = 0. Ground alignment uses the stance-phase median height, not a per-frame clamp (a per-frame clamp would flatten the high jump's flight phase). After alignment the stance-phase foot height IQR is within ±0.5 cm.
- Velocities are stored, low-passed at 20 Hz zero-phase. Most loaders finite-difference them at load time instead, which yields noisier values than these — pick one and be consistent.
Known characteristics and limits
These clips are human motion capture retargeted onto the Master kinematics — no physics engine was involved in producing them. They have been run on the real robot: a whole-body motion-tracking controller follows them successfully on hardware.
Everything below describes the reference trajectory itself, not what the robot can do. A tracking controller approximates a reference; it does not replay it frame-for-frame. So "the reference carries 0.72 g through flight" and "it runs on the real robot" are both true and not in conflict. Read this section before using a clip as a per-frame tracking target, or before assuming a number in it describes the machine.
Flight-phase gravity is 0.72 g
Fitting a parabola to the centre-of-mass height over the middle two thirds of each of
highjump's 5 flight phases gives a vertical acceleration of −7.090 ± 0.057 m/s², not
−9.807 — a consistent 0.723 g. The spread across phases is 0.8 %, so this is systematic,
not noise, and it is a property of the retargeted reference rather than of the robot.
The likely cause is retargeting that rescaled the motion spatially to the robot's proportions while keeping the human's original timing. Froude similarity requires time to scale as √s when length scales by s; s = 0.723 implies the timeline should be compressed by √0.723, i.e. replayed at 120 × 1.176 ≈ 141 Hz. That reading is self-consistent: s = 0.723 against the URDF's 0.602 m standing pelvis height implies a 0.833 m human pelvis, i.e. a subject about 1.57 m tall — a plausible capture subject.
This dataset ships at the source timing, un-retimed. Retiming was tested and does fix the
gravity (−9.843 ± 0.080 m/s², 0.37 % residual), but it pushes a few joints marginally past the
URDF velocity limits (jogging 1/31 at 106 %, highjump 3/31 at 105 %) and raises the jogging
cadence to 195 steps/min. To apply it yourself: resample the timeline by 1.176 and leave the
joint angles untouched.
jogging's contact pattern is a walk, not a run
Cadence is fine (166 steps/min) and swing clearance reaches 22 cm, but each foot is loaded 79 % of the time, double support is 65.6 %, and flight phases have a median of only 17 ms. Real running has a duty factor below 0.5 and 100–200 ms of flight. Good enough as an AMP style prior; per-frame tracking will not teach running dynamics.
highjump's phase structure is sound: 73.8 % double support, 25.5 % airborne, 5 flight phases
with a 400 ms median.
Other limits
- Residual ground penetration at the deepest frames: −1.9 cm (
jogging), −3.6 cm (highjump). - Base pose is not robot-measurable. It comes from the capture system, so it is valid as an offline reference only — never as an observation the robot could produce on its own.
- Joint angles are all within the URDF position limits, and joint velocities stay inside the URDF velocity limits (0/31 violations, peaking at 95 % of the limit). So the clips are kinematically legal; the trajectories are just not rigid-body-consistent on their own, which is normal for retargeted references and is what the tracking controller absorbs.
Validation
python3 validate.py # keys, shapes, quaternion norms, pose_aa round-trip, contact phases,
# and flight-phase gravity computed from the shipped com_pos
Why 120 Hz
The source files carry no sample rate. 120 Hz is inferred from jogging's cadence: the knee
angle's dominant period is 80–86 frames, which at 120 Hz is 166–180 steps/min — the normal
jogging band. 60 Hz would give ~87 steps/min (a stroll) and 240 Hz ~340 (impossible). The
gravity result above suggests the dynamically correct playback rate is ~141 Hz, so treat
120 Hz as the source timing rather than a physically validated one.