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, andfailed_candidates.jsonforrobot-dog-digital-twingates.
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.
- Do not run reinforcement learning or claim sim-to-real stability from this report alone.
- Do not import sibling subskill code. Read files only.
References
references/input-contract.mdforgait_validation.yamlfields.references/gait-levels.mdfor validation levels.references/stability-metrics.mdfor scoring thresholds.references/output-contract.mdfor report fields.references/examples.mdfor sample project layout.