How fast can a belt run before a robot pick cell stops recovering recyclables?

research/infra-sorting

Single-robot conveyor pick cell fed with the class mix and object sizes of the 4,784 TACO litter annotations: with a 1 s pick and 1 m of reach, recovery of bottles and cans holds near 0.65 up to 0.5 m/s, falls to 0.48 at 1.0 m/s and is zero from 1.5 m/s (reach/pick-time is a hard limit); detector size threshold and false-call rate move purity and recovery more than the pick-order policy, which changes nothing.

6 tests

What it found

A discrete-event model of one robot picking bottles and cans (14.9 % of items) from a moving belt, with the item mix and linear sizes taken from the 4,784 annotations of the TACO litter dataset (Proença and Simões 2020). Items arrive as a Poisson stream (3 per metre), stay in a 1 m reach for reach/speed seconds, and are called by a detector whose recall grows with physical size (mean 0.69 on targets). At 1 s per pick, recovery is 0.66 at 0.1 m/s, 0.65 at 0.5, 0.55 at 0.75, 0.48 at 1.0 and zero from 1.5, since an item must stay in reach longer than one pick; the highest speed keeping 80 % of slow-belt recovery is 1.6, 0.8 and 0.4 m/s at 0.5, 1 and 2 s picks. Purity is set by the false-call rate (1.00 at 0, 0.80 at 3 %, 0.38 at 20 %), recovery by the size threshold of the detector (0.79 to 0.39 as it moves from 2 to 8 cm). FIFO, LIFO and largest-first pick orders tie. No detector was trained (no images or GPU here): recall curve, false-call rate, pick time, grasp success, reach and the photo scale are assumed and swept, not fitted; a real cell is not measured.

A figure from its own output

Figure produced by research/infra-sorting: speed — infra-sorting/experiments/speed.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.