Can a G1 humanoid nail a 4x8 sheet lying flat on a table?

What it found

MuJoCo whole-body statics of the Menagerie Unitree G1 pushing a 3.4 kg nailer straight down with its feet planted (reach 0.2–0.8 m, sideways 0–0.8 m, hand height 0.4–1.4 m, pushes of 0, 50 and 100 N, torque and friction limits). A table does not help: at 50 N only 30 of 693 cells are held (94 with no push, none at 100 N), limited by the waist and wrist pitch motors and by the solver’s balance rule. The best plan, with the table top 1.0–1.1 m high and the feet 0.25 m from the edge, reaches 48 of the sheet’s 62 nails in 16 stances, worse than the 13 stances for all 62 on a wall (buildbot-stance); those nails take 43–54 s plus 15 re-stances, equal to the 372 s hand estimate at 23–24 s per re-stance. The push to seat a nail, nailer length, table standoff and re-stance time are swept, not sourced; the IK stays near the home pose with the centre of mass over the feet, so this is an upper bound on difficulty; no collisions, walking or recoil.

A figure from its own output

Paper, code and results

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

More in Robots on the building site

• With the simulated carry and nailing results in place of a swept slowdown, does a stock humanoid pay on a house site?With simulated carry and nailing results in place of a swept slowdown, does a stock humanoid pay on a house site? The H1's carry slowdown is 0.41 to 1.70 against a one-stud labourer (pays in 72% of cells) and 1.63 to 6.82 against a bundle carrier (never pays), against a break-even of 1.07; the dollars are tens per house.
• How long can a Unitree G1 hold a building load before its motors overheat?Can a stock humanoid hold a stud for a minute? G1 static joint torques re-read against a swept continuous-torque fraction: the waist is at 0.54 of peak with empty hands at the carry pose and 0.91 with a 3.8 kg stud, so below a 0.6 continuous ratio nothing is sustainable (0.6 kg at 0.6) and a stud reaches the winding limit in 0.14 thermal time constants at 1/3. A 150-pose search finds a posture (hands 0.15 m ahead, 0.7 m high) at 0.33 of peak, so the 0.91 is not the floor.
• Does a searched posture let a Unitree G1 hold a stud longer than the default pose?Does a searched arm and waist posture let a G1 hold a stud longer? In MuJoCo the stud's peak joint fraction falls from 0.91 (default) to 0.76 with the centre of pressure on the sole point and to 0.49 (best of three noisy seeds) 3 cm inside the toe edge, enough to make a stud sustainable at a continuous rating of 0.5 of peak; a 2x6 goes 0.93 to 0.68 and sheets stay above peak.
• Does a hand-written flexing-sheet plant agree with MuJoCo, and do its sim-to-sim transfer failures hold there?Does the hand-written flexing-sheet plant of buildbot-skills agree with MuJoCo? Pass/fail labels agree on 99.8% of 2600 episodes across 13 policies, so the sim-to-sim transfer failure (0-11% vs 81% where tuned) is not an artefact of my equations.
• Does a G1 humanoid on a drive-and-lift base nail a 4x8 sheet faster than a walking G1?Does a G1 on a drive-and-lift base nail a 4x8 sheet faster than a walking G1? Yes in 22 of 24 speed settings: 54-121 s a sheet (13 stances, 12 moves of 5-63 s) against 85-119 s walking and 372 s by hand, and it matches a 61 s gantry only with a fast tip, 0.5 m/s drive and 0.2 m/s lift (speeds swept, not a chosen machine; reach unchanged from static statics).
• How slow must a person be at nailing a sheet of sheathing for a Unitree G1 nailing it to pay?How slow must a person be at nailing a sheet of sheathing for a Unitree G1 nailing it to pay? A walking G1 (85 s a sheet) pays above 35 s of person time at 0.3 supervision, a base-mounted one above 26 to 76 s; about $110 a house, and the person's time per sheet is the unsourced unknown.

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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.