Ocado Is Boosting Warehouse Efficiency Through Automation

In a bid to address long-standing fulfilment challenges in online grocery and logistics, such as the limitations of traditional robotics and the complexity of picking and packing, Ocado is deploying AI-powered robotic arms.

These robots utilise intelligent sensors and machine vision to accurately pick and pack a wide range of items, including those that are irregularly shaped or fragile. Advanced machine learning (ML) enables the robots to adapt in real time, learning from human demonstrations.

This allows the system to improve warehouse efficiency, driving higher throughput without the need for additional physical space. Ocado’s AI-powered robotic arms reduce dependence on human labour, automate the picking and packing process in fulfilment centres and lower operational costs, shaping the future of logistics.

In a blog, Ocado explains: “OGRP is already providing efficiency at scale for our partners. In 2024, we picked over 30 million items using OGRP and saw huge productivity gains with just a small number of arms installed. Over the next year, we anticipate scaling rapidly. Our experience operating this tech at scale in these environments will continue to differentiate us.

“Our teams continue to leverage the latest breakthroughs in Machine Learning. To expand OGRP’s picking capabilities and understand how to generalise these skills beyond its current applications, we are exploring diffusion – a model which underpins the Gen AI revolution. This will allow us to tap into previously unattainable efficiency levels, as we continue redefining supply chains worldwide.”

Ocado’s AI-powered robotics arms

Ocado’s AI-powered robotic arms are fuelled by On Grid Robotic Pick (OGRP).

This system boosts productivity by extending picking hours, allowing staff redeployment and increasing throughput without widening warehouse footprints.

These arms continuously improve and share knowledge across the fleet as they are trained through reinforced learning and behaviour cloning.

In the long term, Ocado strives to scale this adaptable technology while investing in further Gen AI models to generalise robotic capabilities across international supply chains.

The AI behind the technology

Ocado’s robotic arm technology is powered by a combination of computer vision, machine learning (ML) and sensor-driven intelligence.

Advanced ML models enable the system to generalise across various types of items, learn how to handle products without prior knowledge and make real-time decisions in real-world environments.

These systems foster resilience and flexibility by relying on continuous learning and training data.

Proprietary machine vision systems assist the robots by distinguishing between products and packaging, while also identifying the optimal points to grasp each item.

This vision capability is crucial for ensuring accuracy across a diverse range of SKUs.

Ocado further employs behaviour cloning and reinforcement learning to allow the system to learn from experience, refine its performance and avoid repeating mistakes.

In addition, intelligent pressure and motion sensors help the robots maintain delicate handling, adjusting grip strength as needed to protect fragile items.

The AI robotic arms operate as part of a connected fleet, where learnings from one system can be shared across many. This means that successes or failures can contribute to fleet-wide intelligence, enabling Ocado to scale performance globally.

Ocado’s approach showcases fleet learning, where data from one robotic arm can be used to improve and train others. 

This technology highlights how AI and robotics can unlock improvements in operationally intensive industries like manufacturing.

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