| name | gait-optimization |
| description | Gait validation, scoring, and parameter recommendation for robot-dog virtual
prototypes. Use this skill whenever the user asks whether walking logic is
reasonable, gait parameters are stable, flat-walk/slope tests pass, foot slip is
too high, body roll/pitch is excessive, or the next gait iteration should be proposed.
|
gait-optimization
This skill checks early gait reasonableness for robot-dog virtual prototypes. It
consumes gait parameters and validation metrics, then writes deterministic gait
score, failed-candidate, and next-parameter reports.
When To Use
Use this skill for:
- Single-leg IK, four-leg phase, stand, and flat-walk validation.
- Roll/pitch, foot slip, speed, torque margin, and cost-of-transport scoring.
- Comparing simple candidate gait parameters before deeper simulation.
- Producing
gait_score.json, best_gait_params.yaml, and failed_candidates.json
for robot-dog-digital-twin gates.
Workflow
- Read
<project>/gait_validation.yaml.
- Score current gait validation metrics.
- Mark blockers for falls, failed IK, incomplete phase coverage, unstable posture, high slip, low torque margin, or low speed.
- Score candidate gait parameter sets when present.
- Write reports into
<project>/reports/.
Commands
python skills/gait-optimization/scripts/score_gait.py skills/gait-optimization/examples/quadruped_mvp
python skills/gait-optimization/scripts/search_params.py skills/gait-optimization/examples/quadruped_mvp
python skills/gait-optimization/scripts/write_report.py skills/gait-optimization/examples/quadruped_mvp
Rules
- Keep MVP checks deterministic and conservative.
- Treat failed IK, falling during flat walk, stand time below target, body roll/pitch above limits, foot slip above limit, or torque margin below 20% as blockers.
