AISORT by Xingyao Robotics

Mixed-plastic recovery is often described as a sorting problem. More precisely, it is a confidence problem. A line can only separate material well if it can identify what it is looking at with enough certainty to act on that decision at production speed.

Why single-sensor logic reaches a limit

In straightforward streams, one sensing method may be enough. But once color, shape, contamination, labels, multilayer structure or dirt begin to overlap, single-sensor sorting starts to face ambiguity.

That ambiguity leads to two expensive outcomes: over-rejection, which lowers recovery, and under-rejection, which lowers output quality.

What multi-modal detection changes

Working with difficult mixed streams?

See how fusion-based AISORT platforms can be applied in retrofit and mixed-waste recovery projects.

View fusion platform
Newer Insight Why feedstock preparation defines bottle-to-bottle quality Circular Economy 2026-04-03 Why feedstock preparation determines bottle-to-bottle quality before washing, extrusion and final resin production. Older Insight Why compact AI sorting matters for decentralized recycling centers System Design 2026-04-03 Why compact AI sorting architecture matters as regional and distributed recovery centers expand.

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