Trim highjump to 5 jumps (935 frames); add com_pos/total_mass; update card

README.md

@@ -22,17 +22,18 @@ Interactive viewer: **[Master Motion Sample Space](https://huggingface.co/spaces
 | | |
 |---|---|
 | Clips | 2 (one file each) |
-| Frames | 6563 total |
+| 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.
+**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` | 4739 | 39.5 s | 3.3 MB |
+| `highjump.pkl` | `highjump` | 935 | 7.8 s | 0.7 MB |
 
 ## Loading
 
@@ -45,9 +46,9 @@ d = pickle.load(open("highjump.pkl", "rb"))
 list(d)                            # ['highjump']
 
 m = d["highjump"]
-m["dof"].shape                     # (4739, 31)   joint angles, rad
-m["root_trans_offset"].shape       # (4739, 3)    base position, m
-m["root_rot"].shape                # (4739, 4)    base orientation, xyzw
+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
 ```
 
@@ -110,6 +111,44 @@ pose_aa[t, 1 + j] = dof_axes[j] * dof[t, j]
 These clips come from human motion capture retargeted onto the Master kinematics. No physics
 engine was involved, and they are **not dynamically feasible for the robot as-is**.
 
+### 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.
+
+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). The clips are
+  **kinematically legal but dynamically inconsistent**.
 
 ## Validation
 
@@ -118,3 +157,10 @@ python3 validate.py    # keys, shapes, quaternion norms, pose_aa round-trip, con
                        # 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.

highjump.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:969cb65a4f4859dcc35620b1e34a1ccd9e92239bb96b3225e93aac5cab2a95c0
-size 3338868
+oid sha256:b7cb8f791d6a39a5ef3726b653992d3a05473fc4d1d7369a033e324878715c01
+size 660825