Does a searched posture let a Unitree G1 hold a stud longer than the default pose?

research/buildbot-holdpose

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.

5 tests

What it found

buildbot-holdheat found the G1 waist at 0.54 of peak torque with empty hands at the stud-carry pose and 0.91 with a 3.8 kg stud. The arms are redundant for a fixed hand position and the centre of pressure can move along the foot, so this searches both in MuJoCo (random anchors then a (1+1) evolution strategy, self-collision rejected, three seeds, best kept). With the centre of pressure 3 cm inside the toe edge the default posture gives 0.744 and the best searched posture 0.487 (other seeds 0.63 and 0.68, so the search is noisy and 0.487 is an upper bound on the minimum); a continuous rating of 0.5 of peak then makes the stud sustainable. With the centre of pressure on the sole point the gain is 0.910 to 0.756; at the toe edge 0.586. A 2x6 goes 0.93 to 0.68; sheet, block and drywall cases stay above peak. For a continuous rating of 0.4 or less nothing is sustainable at this pose. Static only; the continuous rating and thermal time constant remain unsourced (swept), the toe edge is read from the model, and the search is weak.

A figure from its own output

Figure produced by research/buildbot-holdpose: figure — buildbot-holdpose/experiments/figure.png, written by the project's own experiment code.

Paper, code and results

More in Robots on the building site

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Other research topics

Proper scoring & elicitation28 Effort & peer prediction9 Verification games & slashing19 Detection & tolerances14 Markets as routers13 Prediction-market design9 Paying contributors8 Decentralised training systems23 Digital twins & sim-to-real164 LLM chip design loops40 Robot manufacturing loops53 Ambient AI assistant46 Self-replicating manufacturing34 Simulation-first design64 Engineered clothing45 Task-specific AI accelerators40 Algorithmic chip-design loops42 Open-source purpose-built robots44 The software-engineering loop43 Adversarial human imitation41 Open-source residential construction41 Autonomous multi-angle capture34 Sensing, imaging and 3D31 Energy supply and dense energy storage39 Robot societies among people31 Agentic co-design of low-cost robots27 Laundry-hanging robots25 Machine learning on qualitative data23 Robots on the building site27 Civilizations & group psychology1 History & 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.