Post on 12-Aug-2015
transcript
17 July 2015
Robots Getting out of Factories and into FieldsIndustrial Automation
9th June
Chris Roberts
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Background
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Overview of Cambridge Consultants
We are a world leader in technology and product innovation
400 engineers, scientists, designers and consultants working from our offices in UK and US For clients world wide, we
– develop breakthrough products & systems
– create and license intellectual property
– provide business consulting in technology critical issues 70% of our work is repeat business – we become trusted partners for our clients
Cambridge MA
Cambridge UK
Singapore
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Agenda
What’s the problem we’re trying to solve here?
Robots are excellent at
– Repetitive tasks
– Hard objects
– Exact dimensions
– Controlled environments
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Agenda
What’s the problem we’re trying to solve here?
Robots are NOT excellent at
– Tasks that change
– Objects that can’t be gripped firmly
– Objects with varying sizes and shapes
– Environments that change
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Future world of work research– 2020 to 2030Will robots steal jobs?
Mature territories
Aging workforce, receding retirement age, expecting better jobs
Networked, integrated warehouse systems
Growing Territories
Highly-mobile workforce with high expectations of a good work-life balance
Increased uptake of control and automation
Emerging Territories
High turnover of young staff with low technical skills
Remote monitoring of warehouses
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Robotics and machine vision
Science vs Engineering
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Robotics case study – Amazon picking challenge
“ The winning design was capable of picking up 12 objects in 20 minutes ”
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Machine vision case study – ArcAid
Measures the arc of the throw in real time Offers rating, advice
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Machine vision case study – ArcAid
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Cambridge Consultants
Robotics Project
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Agenda
Why are we doing this now?
Robotics experience
Low cost sensors and powerful image processing algorithms are available
Embedded processing power
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So, what’s the challenge?
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There are three main technical challenges to picking fruit or vegetables in a warehouse or field:
Grippers / actuators need to cope with softer objects
Algorithms and control systems that can cope without exact models of the environment and objects
Robots that can interact safely with humans
This project focusses on the first two challenges
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Gripper
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Custom gripper design
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Custom gripper design
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Custom gripper design
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Vision Processing
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Vision system
Determine which object is on top of a pile of similar objects Real time processing of the images and depth maps No precise description of the object exists The objects are similar but not identical Low cost, commodity hardware Determine where to place gripper
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Vision system
Load Objects Step Process Images Step
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Vision system
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Process Objects Step
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Vision system
Select Objects Step
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Conclusions
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Getting robots into the field?
Not quite yet – intermediate step
The proof of concept stage is not the hard one
Engineering is as important as the science
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Getting robots into the field?
Embedded processor
RTOS
Vision Driver
Image Processing
Object Detection Robot Movement
Gripper
Vision Sensor
ObjectSensor Driver
Low -level Robot control
Vacuum Control
Gripper Control
Robot Arm
Vacuum Pump and Valves Depth
Sensor
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Getting robots into the field?
Is it worth it?
For some applications it will be – but there needs to be a business case
Development will be expensive
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