Does a 3D-designed hanger keep improving when the end-radius cap is lifted past 6 cm?

What it found

hanger-3dseeds left three of eight 3D-designed optima on its 6 cm end-radius cap. Here the cap is lifted to 10 and 15 cm (M tee, 3 cm half-depth arm, 64 drapes per loop, 8 seeds). Whole-sheet error: 1.08 ± 0.29 cm at 10 cm and 1.21 ± 0.32 at 15 cm, against 1.12 ± 0.25 at 6 cm (differences −0.04 cm, p = 0.77, and +0.08 cm, p = 0.57). Chosen radius grows with the cap (mean 8.2 and 10.6 cm) while crease and sag fall slowly (sag 2.9, 2.2, 1.7 cm), so blunter ends only trade a flat error for smoother drape. Stylised: assumed fabric constants, one 20 cm strip, no friction, one garment and arm depth, a small search budget; a 10 to 15 cm tip is not a usable hanger and no contact-width constraint is applied.

Paper, code and results

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

More in Laundry-hanging robots

• Is a hanger designed in 3D really better than one designed on the 2D centre line, once seed noise is counted?Yes, by 0.26 cm on the whole sheet with hanger-fit's bounds (8 seeds each, p = 0.03) and by 0.68 cm once the end-radius and bow limits are widened (p < 0.001), but the 3D-designed hangers have a worse centre line. Stylised.
• Does a second laundry-hanging arm lose less if it picks a free garment instead of waiting?Does a second laundry-hanging arm lose less if it picks a free garment instead of waiting? At 0.30 m clearance blind pinching recovers 9.5 of its 28 lost garments an hour (151 to 161), aiming about 2 of 10; at 0.45 m nothing. Stylised: clearance and spacing assumed.
• Is a laundry-hanging arm's gain from picking a free garment real? A paired test on 2000 loadsIs a laundry-hanging arm's gain from picking a free garment real? Paired on 2000 loads at 0.30 m: aiming +1.25 an hour (0.60 to 1.92), sweeping +4.4, pinching +10.0; at 0.45 m aiming gains nothing. Stylised: inputs are placeholders.
• How many dryers can one laundry-hanging arm serve once the pick is simulated, not assumed?How many dryers can one laundry-hanging arm serve once the pick is simulated, not assumed? A one-arm cell drops from 169 to 147 garments an hour (5.1 to 4.4 dryers) with look-then-aim picking and to 104 with blind pinching; with two arms the fold table is the limit. Stylised.
• How many dryers can a laundry-hanging arm serve when the fold takes as long as published robots take?How many dryers can a laundry-hanging arm serve when folding takes as long as published robots take? At SpeedFolding's 90–120 s per fold the learned-rule cell falls from 169 to 58–44 garments an hour; always hanging holds 146. Only the fold time is sourced.
• How many dryers can a laundry-hanging cell serve when its fold station runs at published robot speeds?How many dryers can a laundry-hanging cell serve when its fold station runs at published robot speeds? Timed from the SpeedFolding paper (68 to 167 s per garment) rather than an assumed 25 s, one arm and one fold table serve 0.8 to 2.1 dryers instead of 5.1, and with two arms five dryers need 3 to 10 fold tables. Fold times are sourced; every other station time is still assumed.

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.