Robots move in as waste firms struggle to find staff

The dust at this busy recycling plant is pervasive and the steady noise of hoppers and conveyor belts makes this a challenging environment to work in.

The facility in Rainham, east London is owned by Sharp Group, a family-run skip and waste management firm.

Along the conveyor belts runs everything you could imagine, from shoes, to old VHS cassettes and blocks of concrete.

The team here processes up to 280,000 tonnes of mixed recycling every year with 24 agency workers on its rapid conveyor belts.

This is a hazardous industry. While Sharp Group is proud of its safety record, work-related injury and ill-health in the sector is 45% higher than other industries. And the fatality rate is a sizeable multiple of the national average.

These factors, along with the unpleasant nature of the work, mean keeping workers is difficult. Annual staff turnover runs at 40%.

"The belt is moving all the time, you're constantly picking. I go through a lot of pickers because they just aren't up to the job," says line supervisor Ken Dordoy.

The firm rotates pickers through different materials every 20 minutes, and I could see the belt is stopped periodically for respite.

A potential answer to that high-staff turnover, was also on the line when I visited. A robot, known as Alpha (Automated Litter Processing Humanoid Assistant) was being trained to pick through the rubbish.

Built by RealMan Robotics in China, it's being adapted for real-world recycling operations by the British firm TeknTrash Robotics.

Automated robots are not new to the sector, but the use of a humanoid is unusual.

TeknTrash founder and CEO Al Costa argues that copying human movement allows his robot to fit into existing plants without redesigning the machinery.

Alpha is not up to speed yet, instead, it's on a training agenda and being guided through arm movements. Next to it, a plant worker wears a VR headset to record his own endeavours to demonstrate what successful picking and sorting looks like.

The learning process is two-fold. The first is identifying what's on the conveyor and the second part is actually lifting up items.

Costa says this is exactly what early-stage training looks like.

"The market thinks these robots are prêt‑à‑porter, that all you need to do is to plug them to the mains and they will work flawlessly. But they need extensive data in order to be effectively useful."

He showed me how a system called HoloLab delivers data from multiple cameras to train Alpha.

They warn it what's coming, they guide its arms, and they report failures if unpicked items stay on the belt. The passing of thousands of items delivers millions of data points every day.

The training might take time, but if it works, it could make life much easier for the firm.

"The attraction of a humanoid is that you can put it here and it stays here. It will pick all day, 24 hours a day, seven days a week. It's not going to apply for a holiday, it's not going to have a sick day," says Chelsea Sharp, plant finance director and granddaughter of company founder Tom Sharp.

The alternative to this is to build new bespoke plants or retrofit existing facilities with new kit, from companies like Colorado-based AMP.

It runs three of its own plants and has supplied its equipment to dozens of other facilities worldwide, including in Europe and the UK.

CEO Tim Stuart explains that AMP uses air jets to guide items into chutes.

AI is part of the process, as it is constantly improves the way the system identifies and sorts materials.

"Our robots are much more efficient than humans, probably eight or 10 times the pace. The AI technology and jets have really increased the capacity and efficiency and accuracy of what we can do."

California challenger Glacier was co-founded by Rebecca Hu-Thrams. Her company's system uses mounted robotic arms and AI to sort through rubbish.

She points out that the enormous variability of trash is a big challenge for sorting equipment.

Sometimes a beer can will be spraying liquid everywhere, threatening machinery, and her customers have also seen "unbelievable things like hand grenades and firearms coming through their facility".

"As our models learn from more than a billion items, the AI gets better and better," Hu‑Thrams says.

"And we've always designed our technology so it works not just for big urban plants, but for the semi‑rural facilities running on much tighter budgets."

With different approaches, all three companies agree that the human‑intensive model is no longer sustainable.

Across the industry, academics studying waste‑processing say the shift to automation is not only inevitable, but necessary.

As Prof Marian Chertow of Yale University puts it: "Robotics coupled with AI-driven vision systems offers the greatest potential for improving material recovery, worker experience, and economic competitiveness in the recycling sector."

Back in east London, the worker experience is "unappealing", admits Chelsea Sharp.

"This is a really dirty place to work. You can see the dust, you can hear the noise. It's not that nice."

Robots are unbothered by those conditions, but what becomes of the human workers as the technology scales up?

Sharp claims there will be further work opportunities: "The plan is to upskill those staff. They'll be maintaining and overseeing the robots. And it brings those same people away from any dangers, including the unpleasant environment, heavy lifting and noise."