Does the hanger-fit width result survive when its assumed fabric constants are swept two orders of magnitude?

What it found

hanger-fit's drape uses round-number fabric constants. This sweep re-scores its width finding on a full factorial of 162 size M tees (bending rigidity 0.003–1 gf·cm²/cm, weight ×0.5–2, stretch stiffness 40–800 N/m, strip depth 10–30 cm) and one-at-a-time for the child and XXL tees. The best arm half width is the half shoulder + 1 cm in 151 of 162 and + 2 cm in 11, all with stretch stiffness 40 N/m and mostly double weight or a 10 cm strip (best error 0.9–1.7 cm against about 0.2 cm); child and XXL stay at + 1 cm throughout. Bending rigidity alone changes the best error by under 10% (median 0.23–0.25 cm over a 330-fold range). The only sourced input is a patent's range for knit cotton bending rigidity (0.002–0.050, from a search excerpt); stretch, weight and depth ranges are swept, not measured, and vary independently.

A figure from its own output

Paper, code and results

• README and method
• Experiments and results
• Code
• Tests

More in Laundry-hanging robots

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All 25 Laundry-hanging robots projects →

Other research topics

Proper scoring & elicitation28Effort & peer prediction9Verification games & slashing19Detection & tolerances14Markets as routers13Prediction-market design9Paying contributors8Decentralised training systems23Digital twins & sim-to-real164LLM chip design loops40Robot manufacturing loops53Ambient AI assistant46Self-replicating manufacturing34Simulation-first design64Engineered clothing45Task-specific AI accelerators40Algorithmic chip-design loops42Open-source purpose-built robots44The software-engineering loop43Adversarial human imitation41Open-source residential construction41Autonomous multi-angle capture34Sensing, imaging and 3D31Energy supply and dense energy storage39Robot societies among people31Agentic co-design of low-cost robots27Laundry-hanging robots25Machine learning on qualitative data23Robots on the building site27Civilizations & group psychology1History & human sciences1

Produced with AI assistance (Claude). Results are from the code in this repository and are simulated or stylised unless the abstract says otherwise; nothing here implies affiliation with or endorsement by any lab, researcher or company cited. MIT licensed.