microduck-tricks / docs /roller_glide_plan.md

Microduck tricks: elan roulade, cone slalom, single-blade lift (policies, docs, clips)

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# Single-blade glide — retrospective and the next plan (2026-09-04)

Nine runs (v6–v12b, ≈ $27 of L4 time) did not produce a sustained single-blade glide; the
two-feet phase and the glide command channel are solved (v9 2750, v10 3750: 0/6 falls on all
four held-out protocols). Full evidence per version: `roller_glide.md`.

## Root causes (measured)

1. **No feasible successes to learn from.** Prices (fall −100 → −30, switch tax 2 → 6, hold
   weight 10 → 16) never changed held-out behaviour: with a fall price the policy pumps, without
   one it attempts and collapses. RL needs on-policy successes; nothing supplied them.
2. **The born-gliding spawn is a state, not a skill.** v6 held 0.8 s using the free folded leg as
   a counterweight; frozen (v11) it falls sideways at 0.40 s, 8/8. `scripts/probe_single_blade_balance.py`:
   the passive folded pose rolls 2.5 s before pitching forward; 126 hand-tuned PD gain sets found
   no rolling one-blade balance (survivors stopped and put the foot down).
3. **A training metric was misread all night.** `glide_frontier ≈ 0.009` was taken as "no holds";
   `scripts/audit_glide_gates.py` (v6-2000 back inside the v6 env) shows the gates count 70 % of
   steps and training streaks reach 0.3–0.6 s — the value is just per-step normalised. The held-out
   battery is the only criterion; training holds from the spawn did not transfer to the command.
4. **Physics:** no ankle roll, 5 cm inline wheelbase → bicycle-like balance (hip roll for the CoM,
   hip yaw to steer into the lean) with a 5 cm fore–aft margin.
5. **Process:** spawn-height, lock and pacing failures were all measurable on CPU before launch;
   a network outage killed every waiter; four runs tested the same price hypothesis.

## Plan — prove feasibility first, then let RL learn it

| stage | what | gate |
|---|---|---|
| 0 (CPU, 1 day, $0) | Model-based expert (hip pitch/ankle for the fore–aft margin, hip roll + hip yaw for lateral balance; trajectory optimisation if PD fails) from the v6 pose; in parallel a **scooter** definition (swing foot skims 1–2 cm, occasional touches allowed). Output: an expert trajectory bank (joints, velocities, attitude, wheel spins, random phase). | ≥ 3 s one-blade rolling at ≥ 0.2 m/s, 8/10 under perturbation, for either definition — otherwise the hardware cannot do a strict single-blade glide: pick the scooter definition or a hardware change, do not train. |
| 1 (1 night, ≈ $4) | v10 base (skate-state spawns, gentle hold ramp, fall −30, switch tax 6) + glide spawns at random phases of the expert trajectories (a true reverse curriculum from feasible states, share 0.7) + a wide-std Gaussian tracking of the expert's stance-leg joints and trunk attitude during the glide phase; four-protocol battery every 250 iterations, selection by the battery only. | born protocol hold ≥ 1.5 s with ≤ 10 % falls; ≥ 1 s holds from the rolling start. |
| 2 (1 night, ≈ $4) | Entry/exit with the existing phase-command infrastructure, initialised from stage 1, spawn mix shifting to two-feet starts; slewed internal target for the exit. | rolling-start and hot-swap protocols: hold ≥ 1.5 s, ≤ 10 % falls, skates on after the exit. Then the video. |
| 3 (fallback) | DAgger-style distillation from the expert, then RL fine-tuning; or ship the scooter definition. | — |

Process rules for the next round: CPU spawn-geometry audit + reward-gate audit + 64-env smoke
before every launch; one hypothesis per run, taken from held-out measurements; network-tolerant
waiters (`robust_sweep.sh`) with results written to the repo; no weight step above ×1.5, stop
and roll back on any metric drop at a stage boundary; feasibility before RL.

## Stage 0 findings (2026-09-04)

* **Strict single blade (swing foot up): not reachable even for a model-based controller.**
  `scripts/expert_single_blade.py` (CEM over a linear law on CoM-vs-blade offsets, trunk attitude
  and rates; stance hip roll/yaw/pitch/ankle + swing hip roll; searched fold strength): best laws
  survive 0.3–1.2 s, robustness 0/10, three searches (two strict, one scooter-as-single).
* **Why — actuator limits, measured** (`scripts/probe_actuator_limits.py`): holding the born
  pose, the folded swing foot sags to 4–8 mm above the floor and touches on most steps at every
  commanded fold strength (servo tracking error 0.3–0.5 rad on knee/hip); pulling harder shifts
  the CoM and tips the duck in 0.4–0.6 s. The stance hip-roll step response has a 0.22 s 63 %
  rise time (with overshoot) against a ≈ 0.1 s lateral pendulum — CoM-shift balance on one
  blade is outside the XL330 servo's bandwidth on this geometry.
* Consequence: the whole v6–v12b family was in fact practising a *skimming* foot (≤ 1 cm
  clearance); the 1 cm training gate was at the edge of what the hardware can do.
* **Definition B (scooter glide: one leg visibly folded and unloaded, its tire may skim)** is
  being measured next with contact forces (`scripts/expert_scooter.py`).

### The decisive measurement: the born-gliding pose was never single support

`scripts/probe_single_blade_geometry.py` (contact forces, held pose, rolling at 0.35 m/s):

| stance hip-roll (evaluator sign) | lean | CoM − stance blade (lateral) | swing-foot load | stance load | passive survival |
|---|---|---|---|---|---|
| **+0.25 (v6 and every run since)** | 7° | **+5.5 cm** | **66 %** | 21 % | 2.5 s (falls forward) |
| +0.60 | 7° | +8.3 cm | 66 % | 22 % | 4 s+ (standing on the folded foot, 0.03 m/s) |
| −0.25 | 7° | +0.9 cm | 15 % | 64 % | 0.34 s |
| **−0.40** | 7° | **−0.5 cm** | **0 %** | **74 %** | 0.32 s (a true inverted pendulum) |

With the sign the whole family used, the folded foot sits under the body and carries two thirds
of the weight — the "0.8 s holds" of v6 were standing on the *lifted* leg's tire. The `shift`
parameter translates the whole robot (feet included) and never moved the CoM over the blade.
The training spawn (`V6_STANCE_LEFT = {1: +0.25}` / `V6_STANCE_RIGHT = {10: −0.25}`) has the
same sign, so the training never saw a single-blade state either — and the actuator-bandwidth
conclusion above was drawn on the wrong posture. With the stance hip-roll reversed (−0.3 to
−0.4) the stance blade is under the CoM, the swing foot is 46 mm up and unloaded: the real
balance problem, which the expert search now attacks from a balanced start.

From the corrected spawn the same CEM law (`--stance-roll -0.3 --lean 7 --shift 0`) rides one
blade for 0.8–1.06 s at 0.5–0.8 m/s with 90–98 % single support and the swing tire ≤ 15 % of
steps on the floor — the first genuine single-blade glides of the whole effort — and then
falls; the search plateaus at 0.8 s (0/10 reach 3 s). Next oracle: sampling MPC
(`scripts/mppi_single_blade.py`, perfect model, full state, 0.3 s lookahead) at 0.35 and
0.2 m/s. `Mjlab-RollerGlideV13-Flat-MicroDuck` carries the corrected spawn sign into training
(`V13_STANCE_LEFT = {1: −0.3}`, `V13_STANCE_RIGHT = {10: +0.3}`, no root shift).

### Stage 0 verdict (2026-09-04, evening)

Every controller that has the full state and the perfect model tops out at the same place:

| controller | posture | true single-blade time | notes |
|---|---|---|---|
| v6 RL policy (ckpt 2000), old spawn | policy-corrected | 0.80 s max, 88 % true single (load-based) | falls 3/6 |
| CEM linear law, corrected spawn, 0.35 m/s | stance under CoM | 0.8–1.06 s | lateral CoM drift +12 cm in 0.8 s with the stance hip roll saturated |
| CEM linear law, 0.6 m/s (steering authority) | same | 0.5–0.9 s | no gain from speed |
| MPPI (128 samples, 0.4 s horizon) around the best posture | same | 0.68–0.76 s | perfect model, still ≤ 1 s |

The load-based metric (`eval_single_blade.py`, one blade ≥ 90 % of the ground force) confirms the
v6 holds were real single support once the policy lifted the leg — the passive spawn sag was a
red herring for the *policy*, but it was real for every held-pose probe. The binding limit is
lateral authority: the stance hip roll can shift the CoM only 1–2 cm, steering at these speeds
buys a few degrees, there is no ankle roll, and the trunk+leg pendulum diverges in ~0.3 s.
**Verdict: a sustained (≥ 3 s) one-blade glide is not reachable on this robot in this simulator.
The reachable skill is a ~0.8–1.0 s one-blade glide, entered from skating and exited by placing
the foot down before the fall.** That is the target proposed for stage 1.

## Stage 1 build (2026-09-04): `Mjlab-RollerGlideV14-Flat-MicroDuck`

Target: lift a foot while skating, ride one blade ~1 s, put it down before the fall, no falls.
On v13 (v10's stable base + the corrected spawn sign): the single-support gate of every glide
term is now measured by contact load (one blade ≥ 90 % of the ground force); a `glide_exit`
reward (weight 10) pays once when a streak ≥ 0.6 s ends by the foot coming down upright;
commanded glide phases last 0.8–1.5 s; half of the born-gliding envs spawn from the stage-0
expert's mid-glide states (692 true-single states, mirrored for the right-swing side). In-env
check (`scripts/validate_glide_spawns.py`): 16 / 16 born-gliding envs start in true single
support on the intended blade and the gate counts all 16. Launch is waiting on HF Jobs credits
(the namespace is at zero).

### v14 at 1500 (held-out, short command, n = 6–12)

| start | falls | TRUE single-blade bout max | note |
|---|---|---|---|
| corrected born pose, command 0–1.2 s | 0 / 12 (ckpt 750 and 1500) | 0.48–0.70 s (ckpt 750: 2 / 6 trials ≥ 0.6 s) | holds, then puts the foot down cleanly |
| rolling start, command 2–3.2 s | 0 / 6 at every checkpoint | 0.22–0.30 s | lifts briefly, does not commit |
| hot-swap from the official skater | 0 / 6 | 0.20–0.30 s | same |
| standing start | 0 / 6 | 0.26–0.30 s | same |

The put-down bonus (fixed, ≥ 0.6 s) never fired in training (`glide_exit` = 0.000 in every
window): the policy's bouts from a skating start sit at 0.3 s, below the threshold, so the
bonus gave no gradient. v15 (launched 15:47 PT, L4 + A10G hedge) pays the put-down in
proportion to the bout it ends (min(bout, 1 s)/1 s from 0.2 s, weight 15) and ramps the hold
6 → 9 → 12; v14 keeps running to 4000 for comparison.

### v14 final (4000 iterations, A10G, completed 17:40 PT)

From every skating start (rolling, standing, hot-swap) the TRUE single-blade bout stays at
0.18–0.44 s at all 16 checkpoints with 0 falls: the policy lifts briefly and never commits.
From the corrected born pose it commits at two checkpoints (2250: 6/6 trials ≥ 0.6 s, 0.74 s
max; 3999: 5/6, 0.80 s) — and falls in 6/6 and 5/6 of those trials. The two behaviours the
target needs (commit for ~1 s, then put the foot down) never coexist in v14. v15 (graded
put-down bonus) is being swept; v16 (dense entries: first command from 0.3 s, two commands per
episode) is built and smoke-tested, waiting for credits.

### Interim deliverable (2026-09-04, 18:20 PT)

Seeded takes (renderer `--seed`, standing start, command at 3.0–4.2 s, side camera): v15
checkpoint 1250 lifts a foot 0.30–0.34 s of true single-blade support in 10 / 10 takes with
no falls; v14 2000 with the official skater's hand-off 0.34–0.40 s, 10 / 10 no falls. Saved to
the Desktop as `microduck_single_leg_glide_v15-1250_take1.mp4` (+ a 0.25× slow-motion cut of
the lift). This is the honest current state: a visible lift-and-glide of a third of a second,
entered from skating and exited cleanly — not yet the ~1 s the physics allows.

### v15 final (4000 iterations, A10G, completed 18:35 PT)

| start | TRUE single-blade bout max (best checkpoints) | falls |
|---|---|---|
| corrected born pose | 0.94 s (3000, 4/6 trials ≥ 0.6 s), 1.18 s (3250, 3/6) | 1/6, 2/6 |
| rolling (bank) start | 0.50–0.54 s (1750, 2000, 2500) | 0–2/6 |
| standing start | 0.66 s (1750, 1/6; 2/6 falls), 0.44 s (2000, 0 falls) | — |
| hot-swap from the official skater | 0.24–0.40 s | 0–1/6 |

The graded put-down bonus pushed the born-pose hold to the physical ceiling (≈ 1 s) and
lengthened the lift from skating only marginally (0.3 → 0.5 s). The entry from skating is
still the missing skill; each episode offers one attempt at it. v16 (two commands per episode,
first from 0.3 s) is the next run once credits allow.

### Delivered video (2026-09-04, 19:05 PT)

Seeded takes of v15 checkpoints 1750 / 2000 / 2500 from a standing start (8 seeds each, command
at 3.0–4.2 s): the longest clean lift is v15 1750 seed 7 — 0.64 s of true single-blade support
(lift at 3.96 s), no fall; seeds 2 and 5 give 0.58 s; 2000 tops out at 0.46 s, 2500 at 0.40 s.
`~/Desktop/microduck_single_leg_glide.mp4` (+ `_slowmo.mp4`, 0.25× on 3.6–5.0 s) is that take.

	# Single-blade glide — retrospective and the next plan (2026-09-04)

	Nine runs (v6–v12b, ≈ $27 of L4 time) did not produce a sustained single-blade glide; the
	two-feet phase and the glide command channel are solved (v9 2750, v10 3750: 0/6 falls on all
	four held-out protocols). Full evidence per version: `roller_glide.md`.

	## Root causes (measured)

	1. No feasible successes to learn from. Prices (fall −100 → −30, switch tax 2 → 6, hold
	weight 10 → 16) never changed held-out behaviour: with a fall price the policy pumps, without
	one it attempts and collapses. RL needs on-policy successes; nothing supplied them.
	2. The born-gliding spawn is a state, not a skill. v6 held 0.8 s using the free folded leg as
	a counterweight; frozen (v11) it falls sideways at 0.40 s, 8/8. `scripts/probe_single_blade_balance.py`:
	the passive folded pose rolls 2.5 s before pitching forward; 126 hand-tuned PD gain sets found
	no rolling one-blade balance (survivors stopped and put the foot down).
	3. A training metric was misread all night. `glide_frontier ≈ 0.009` was taken as "no holds";
	`scripts/audit_glide_gates.py` (v6-2000 back inside the v6 env) shows the gates count 70 % of
	steps and training streaks reach 0.3–0.6 s — the value is just per-step normalised. The held-out
	battery is the only criterion; training holds from the spawn did not transfer to the command.
	4. Physics: no ankle roll, 5 cm inline wheelbase → bicycle-like balance (hip roll for the CoM,
	hip yaw to steer into the lean) with a 5 cm fore–aft margin.
	5. Process: spawn-height, lock and pacing failures were all measurable on CPU before launch;
	a network outage killed every waiter; four runs tested the same price hypothesis.

	## Plan — prove feasibility first, then let RL learn it

	\| stage \| what \| gate \|
	\|---\|---\|---\|
	\| 0 (CPU, 1 day, $0) \| Model-based expert (hip pitch/ankle for the fore–aft margin, hip roll + hip yaw for lateral balance; trajectory optimisation if PD fails) from the v6 pose; in parallel a scooter definition (swing foot skims 1–2 cm, occasional touches allowed). Output: an expert trajectory bank (joints, velocities, attitude, wheel spins, random phase). \| ≥ 3 s one-blade rolling at ≥ 0.2 m/s, 8/10 under perturbation, for either definition — otherwise the hardware cannot do a strict single-blade glide: pick the scooter definition or a hardware change, do not train. \|
	\| 1 (1 night, ≈ $4) \| v10 base (skate-state spawns, gentle hold ramp, fall −30, switch tax 6) + glide spawns at random phases of the expert trajectories (a true reverse curriculum from feasible states, share 0.7) + a wide-std Gaussian tracking of the expert's stance-leg joints and trunk attitude during the glide phase; four-protocol battery every 250 iterations, selection by the battery only. \| born protocol hold ≥ 1.5 s with ≤ 10 % falls; ≥ 1 s holds from the rolling start. \|
	\| 2 (1 night, ≈ $4) \| Entry/exit with the existing phase-command infrastructure, initialised from stage 1, spawn mix shifting to two-feet starts; slewed internal target for the exit. \| rolling-start and hot-swap protocols: hold ≥ 1.5 s, ≤ 10 % falls, skates on after the exit. Then the video. \|
	\| 3 (fallback) \| DAgger-style distillation from the expert, then RL fine-tuning; or ship the scooter definition. \| — \|

	Process rules for the next round: CPU spawn-geometry audit + reward-gate audit + 64-env smoke
	before every launch; one hypothesis per run, taken from held-out measurements; network-tolerant
	waiters (`robust_sweep.sh`) with results written to the repo; no weight step above ×1.5, stop
	and roll back on any metric drop at a stage boundary; feasibility before RL.

	## Stage 0 findings (2026-09-04)

	* Strict single blade (swing foot up): not reachable even for a model-based controller.
	`scripts/expert_single_blade.py` (CEM over a linear law on CoM-vs-blade offsets, trunk attitude
	and rates; stance hip roll/yaw/pitch/ankle + swing hip roll; searched fold strength): best laws
	survive 0.3–1.2 s, robustness 0/10, three searches (two strict, one scooter-as-single).
	* Why — actuator limits, measured (`scripts/probe_actuator_limits.py`): holding the born
	pose, the folded swing foot sags to 4–8 mm above the floor and touches on most steps at every
	commanded fold strength (servo tracking error 0.3–0.5 rad on knee/hip); pulling harder shifts
	the CoM and tips the duck in 0.4–0.6 s. The stance hip-roll step response has a 0.22 s 63 %
	rise time (with overshoot) against a ≈ 0.1 s lateral pendulum — CoM-shift balance on one
	blade is outside the XL330 servo's bandwidth on this geometry.
	* Consequence: the whole v6–v12b family was in fact practising a skimming foot (≤ 1 cm
	clearance); the 1 cm training gate was at the edge of what the hardware can do.
	* Definition B (scooter glide: one leg visibly folded and unloaded, its tire may skim) is
	being measured next with contact forces (`scripts/expert_scooter.py`).

	### The decisive measurement: the born-gliding pose was never single support

	`scripts/probe_single_blade_geometry.py` (contact forces, held pose, rolling at 0.35 m/s):

	\| stance hip-roll (evaluator sign) \| lean \| CoM − stance blade (lateral) \| swing-foot load \| stance load \| passive survival \|
	\|---\|---\|---\|---\|---\|---\|
	\| +0.25 (v6 and every run since) \| 7° \| +5.5 cm \| 66 % \| 21 % \| 2.5 s (falls forward) \|
	\| +0.60 \| 7° \| +8.3 cm \| 66 % \| 22 % \| 4 s+ (standing on the folded foot, 0.03 m/s) \|
	\| −0.25 \| 7° \| +0.9 cm \| 15 % \| 64 % \| 0.34 s \|
	\| −0.40 \| 7° \| −0.5 cm \| 0 % \| 74 % \| 0.32 s (a true inverted pendulum) \|

	With the sign the whole family used, the folded foot sits under the body and carries two thirds
	of the weight — the "0.8 s holds" of v6 were standing on the lifted leg's tire. The `shift`
	parameter translates the whole robot (feet included) and never moved the CoM over the blade.
	The training spawn (`V6_STANCE_LEFT = {1: +0.25}` / `V6_STANCE_RIGHT = {10: −0.25}`) has the
	same sign, so the training never saw a single-blade state either — and the actuator-bandwidth
	conclusion above was drawn on the wrong posture. With the stance hip-roll reversed (−0.3 to
	−0.4) the stance blade is under the CoM, the swing foot is 46 mm up and unloaded: the real
	balance problem, which the expert search now attacks from a balanced start.

	From the corrected spawn the same CEM law (`--stance-roll -0.3 --lean 7 --shift 0`) rides one
	blade for 0.8–1.06 s at 0.5–0.8 m/s with 90–98 % single support and the swing tire ≤ 15 % of
	steps on the floor — the first genuine single-blade glides of the whole effort — and then
	falls; the search plateaus at 0.8 s (0/10 reach 3 s). Next oracle: sampling MPC
	(`scripts/mppi_single_blade.py`, perfect model, full state, 0.3 s lookahead) at 0.35 and
	0.2 m/s. `Mjlab-RollerGlideV13-Flat-MicroDuck` carries the corrected spawn sign into training
	(`V13_STANCE_LEFT = {1: −0.3}`, `V13_STANCE_RIGHT = {10: +0.3}`, no root shift).

	### Stage 0 verdict (2026-09-04, evening)

	Every controller that has the full state and the perfect model tops out at the same place:

	\| controller \| posture \| true single-blade time \| notes \|
	\|---\|---\|---\|---\|
	\| v6 RL policy (ckpt 2000), old spawn \| policy-corrected \| 0.80 s max, 88 % true single (load-based) \| falls 3/6 \|
	\| CEM linear law, corrected spawn, 0.35 m/s \| stance under CoM \| 0.8–1.06 s \| lateral CoM drift +12 cm in 0.8 s with the stance hip roll saturated \|
	\| CEM linear law, 0.6 m/s (steering authority) \| same \| 0.5–0.9 s \| no gain from speed \|
	\| MPPI (128 samples, 0.4 s horizon) around the best posture \| same \| 0.68–0.76 s \| perfect model, still ≤ 1 s \|

	The load-based metric (`eval_single_blade.py`, one blade ≥ 90 % of the ground force) confirms the
	v6 holds were real single support once the policy lifted the leg — the passive spawn sag was a
	red herring for the policy, but it was real for every held-pose probe. The binding limit is
	lateral authority: the stance hip roll can shift the CoM only 1–2 cm, steering at these speeds
	buys a few degrees, there is no ankle roll, and the trunk+leg pendulum diverges in ~0.3 s.
	**Verdict: a sustained (≥ 3 s) one-blade glide is not reachable on this robot in this simulator.
	The reachable skill is a ~0.8–1.0 s one-blade glide, entered from skating and exited by placing
	the foot down before the fall.** That is the target proposed for stage 1.

	## Stage 1 build (2026-09-04): `Mjlab-RollerGlideV14-Flat-MicroDuck`

	Target: lift a foot while skating, ride one blade ~1 s, put it down before the fall, no falls.
	On v13 (v10's stable base + the corrected spawn sign): the single-support gate of every glide
	term is now measured by contact load (one blade ≥ 90 % of the ground force); a `glide_exit`
	reward (weight 10) pays once when a streak ≥ 0.6 s ends by the foot coming down upright;
	commanded glide phases last 0.8–1.5 s; half of the born-gliding envs spawn from the stage-0
	expert's mid-glide states (692 true-single states, mirrored for the right-swing side). In-env
	check (`scripts/validate_glide_spawns.py`): 16 / 16 born-gliding envs start in true single
	support on the intended blade and the gate counts all 16. Launch is waiting on HF Jobs credits
	(the namespace is at zero).

	### v14 at 1500 (held-out, short command, n = 6–12)

	\| start \| falls \| TRUE single-blade bout max \| note \|
	\|---\|---\|---\|---\|
	\| corrected born pose, command 0–1.2 s \| 0 / 12 (ckpt 750 and 1500) \| 0.48–0.70 s (ckpt 750: 2 / 6 trials ≥ 0.6 s) \| holds, then puts the foot down cleanly \|
	\| rolling start, command 2–3.2 s \| 0 / 6 at every checkpoint \| 0.22–0.30 s \| lifts briefly, does not commit \|
	\| hot-swap from the official skater \| 0 / 6 \| 0.20–0.30 s \| same \|
	\| standing start \| 0 / 6 \| 0.26–0.30 s \| same \|

	The put-down bonus (fixed, ≥ 0.6 s) never fired in training (`glide_exit` = 0.000 in every
	window): the policy's bouts from a skating start sit at 0.3 s, below the threshold, so the
	bonus gave no gradient. v15 (launched 15:47 PT, L4 + A10G hedge) pays the put-down in
	proportion to the bout it ends (min(bout, 1 s)/1 s from 0.2 s, weight 15) and ramps the hold
	6 → 9 → 12; v14 keeps running to 4000 for comparison.

	### v14 final (4000 iterations, A10G, completed 17:40 PT)

	From every skating start (rolling, standing, hot-swap) the TRUE single-blade bout stays at
	0.18–0.44 s at all 16 checkpoints with 0 falls: the policy lifts briefly and never commits.
	From the corrected born pose it commits at two checkpoints (2250: 6/6 trials ≥ 0.6 s, 0.74 s
	max; 3999: 5/6, 0.80 s) — and falls in 6/6 and 5/6 of those trials. The two behaviours the
	target needs (commit for ~1 s, then put the foot down) never coexist in v14. v15 (graded
	put-down bonus) is being swept; v16 (dense entries: first command from 0.3 s, two commands per
	episode) is built and smoke-tested, waiting for credits.

	### Interim deliverable (2026-09-04, 18:20 PT)

	Seeded takes (renderer `--seed`, standing start, command at 3.0–4.2 s, side camera): v15
	checkpoint 1250 lifts a foot 0.30–0.34 s of true single-blade support in 10 / 10 takes with
	no falls; v14 2000 with the official skater's hand-off 0.34–0.40 s, 10 / 10 no falls. Saved to
	the Desktop as `microduck_single_leg_glide_v15-1250_take1.mp4` (+ a 0.25× slow-motion cut of
	the lift). This is the honest current state: a visible lift-and-glide of a third of a second,
	entered from skating and exited cleanly — not yet the ~1 s the physics allows.

	### v15 final (4000 iterations, A10G, completed 18:35 PT)

	\| start \| TRUE single-blade bout max (best checkpoints) \| falls \|
	\|---\|---\|---\|
	\| corrected born pose \| 0.94 s (3000, 4/6 trials ≥ 0.6 s), 1.18 s (3250, 3/6) \| 1/6, 2/6 \|
	\| rolling (bank) start \| 0.50–0.54 s (1750, 2000, 2500) \| 0–2/6 \|
	\| standing start \| 0.66 s (1750, 1/6; 2/6 falls), 0.44 s (2000, 0 falls) \| — \|
	\| hot-swap from the official skater \| 0.24–0.40 s \| 0–1/6 \|

	The graded put-down bonus pushed the born-pose hold to the physical ceiling (≈ 1 s) and
	lengthened the lift from skating only marginally (0.3 → 0.5 s). The entry from skating is
	still the missing skill; each episode offers one attempt at it. v16 (two commands per episode,
	first from 0.3 s) is the next run once credits allow.

	### Delivered video (2026-09-04, 19:05 PT)

	Seeded takes of v15 checkpoints 1750 / 2000 / 2500 from a standing start (8 seeds each, command
	at 3.0–4.2 s): the longest clean lift is v15 1750 seed 7 — 0.64 s of true single-blade support
	(lift at 3.96 s), no fall; seeds 2 and 5 give 0.58 s; 2000 tops out at 0.46 s, 2500 at 0.40 s.
	`~/Desktop/microduck_single_leg_glide.mp4` (+ `_slowmo.mp4`, 0.25× on 3.6–5.0 s) is that take.