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Robot manufacturing loops

Does the time-optimal carry's edge over a tuned trapezoid survive when torque or the jaw cap binds?

research/robofab-torquebound

Re-checks the torque- and jaw-bound rows of robofab-scurve (no speed limit) with a converged solver and denser trapezoid ramp sampling: the time-optimal carry is still 9.4 to 23.0% faster than the tuned trapezoid in all 9 rows, and the edge is stable to solver node count (under 0.1%) and rises by at most 0.4 points with denser sampling. Stylised.

50 tests

What it found

Follow-up to robofab-toppconv (stylised, preliminary). The nine no-speed-limit rows of robofab-scurve (three arm sizes, jaw cap 2×, 5× or none, six printed parts each) are recomputed with the time-optimal solver at 400 to 25600 nodes and the trapezoid on a fine ramp grid with 40 and 160 extra samples per ramp. The time-optimal carry is 9.4% to 23.0% faster than the trapezoid in every row; the solver is converged to within 0.004% by 6400 nodes, and denser ramp sampling slows the trapezoid by 0.05% to 0.5%, raising the edge by at most 0.4 points. So, unlike the sub-1% edge under a speed limit, the torque- and jaw-bound gap is not a resolution artefact in this toy. A trapezoid-only comparison on assumed parameters; not a claim about real arms.

A figure from its own output

Figure produced by research/robofab-torquebound: edge
robofab-torquebound/experiments/edge.svg, written by the project's own experiment code.

Paper, code and results

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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.