some cognitive robotics applications and challenges at...

Dr Graham Deacon

Robotics Research Team Leader

Ocado Technology

Some Cognitive Robotics Applications and

Challenges at Ocado

Outline of Talk

• A bit of background about Ocado.

• A brief look at the automation currently used in our warehouses to fulfil orders.

• Two case studies:-

• Maintenance technician assistant: EU H2020 project SecondHands

• Dolly marshalling using intelligent autonomous vehicles

Ocado confidential information - not to copied or retransmitted

Ocado’s business

Online only grocery retailer

No shops!

Orders placed online

Highly automated warehouses in Hatfield (Hertfordshire) and Dordon

(Warwickshire)

Delivered to customers by our own fleet in guaranteed 1 hour time slots

Scale

~2 million items picked per day

~270,000 orders per week

~45,000 distinct SKUs

10,000 employees

650 in Ocado Technology (want 800 this time next year)

(Very unusual profile for a retailer.)


Customer Fulfilment Centre Automation

Hub and spoke model – 2 large warehouses (CFCs), 10 spokes.

• Hatfield CFC contains >25km of conveyor, with 275 pick stations, ~1000 crossover

points, ~3000 barcode scanners.

• Dordon CFC contains >25km of conveyor, with 250 pick stations, ~1000 crossover

points, ~3000 barcode scanners.


Video of delivery totes in the Hatfield CFC


<Video removed>


Case study 1: Maintenance Technician

Assistant – H2020 project SecondHands

• Currently Ocado use a team of human

maintenance technicians to maintain the

warehouse automation (conveyor, transfers,

lifts and cranes)

• The idea for SecondHands originates from

the realization that most of the tasks

involved in the maintenance work are quite

predictable (semi structured environment),

and would actually benefit from two people

cooperating to perform them.

Ocado Technology (Coordinator)

University College London

Karlsruhe Institute of Technology

École Polytechnique Fédérale de

Lausanne

Sapienza University of Rome


• Humans working collaboratively on

a task like maintenance of

automation, predominantly do so

without needing to form an

agreement about who does what for

every activity. Humans anticipate in

order to work pro-actively.

• Called “SecondHands” because we

want the robot to act as a second

pair of hands that a maintenance

technician can rely on.


We are developing a framework for

modelling technician behaviour so that

the robot can:-

• Understand the scope of the task

• Recognise where in a task the

technician is

• Understand when it can usefully

provide assistance.

• Dynamically replan when conditions

change

• Know if it doesn’t know something

In essence the robot needs to know what

to do, when to do it, and how to do it, in a

manner that a human can depend on.


Case study 2: Dolly Marshalling

What is a dolly?


Use AGVs to automate marshalling


Frameloading

<Video removed>


Dekit and storage

<Video removed>


Loading bay

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Problems to be addressed

Large scale model construction of static environmental elements.

Vision systems need to be robust in the face of variation in illumination and

reflective objects.

Localisation, navigation, path planning and obstacle avoidance in a dynamic

environment.

Need to identify and track people and dollies and predict their behaviour.

Learning what is “normal” in order to perform anomaly detection.

Division of decisions between global and local perspectives.

Degree of competition versus cooperation.


Questions?

some cognitive robotics applications and challenges at...

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