Can robots help us recycle?

New hope from AI

The gap between what’s collected and what’s recycled has led to huge investments in automated

solutions that use AI and machine learning to separate mixed recyclables at waste treatment plants.

The goal of these technologies is threefold – to improve the quality and purity of shipped secondary

commodities, to decrease the cost of labour, and to increase safety for human workers.

Norwegian multinational corporation TOMRA, Finnish robotics giant ZenRobotics and Canadian

sorting specialist Machinex are all enterprises committed to providing bespoke sensor-based solutions

to the recycling industry. All these companies offer robotic arms that use computer vision systems,

spectroscopic cameras and data supplied from sensors to separate items on a conveyor belt based on

their perceive size, shape, colour and conductivity level.

These solutions proved to be at least double as fast as a human worker and equally accurate in

recognising different materials. For example, an optical sorter produced by Machinex can sort

recyclables at up to 3,000 objects per minute, while the average of a human worker is 800.

The human angle

Currently, human operators are still needed to dispose of what machines fail to recognise, since

misidentified items can not only contaminate the purity of recyclable material, but also ruin expensive

equipment. For example, overlooked metal or glass objects can sneak in a paper-processing spinning

machine and damage it.

However, it’s extremely difficult to find and retain a workforce for this job, since manually sorting

trash is a monotonous, unpleasant and often hazardous task. As a consequence, waste treatment plants

report that many employees quit within hours. AI-based solutions would allow plant managers to reassign

their employees to more qualified and rewarding positions, while robots would take care or the most

menial and dangerous tasks.

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