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How AI will increase the performance
and capabilities
of AMRsJosh Cloer – Sales Director
Mobile Industrial Robots
WhatWhenWhereWhyHow
is Artificial Intelligence?
did AI ‘start’?
will AI be useful for AMR?
is AI important for AMR?
will AI change robotics?
What is Artificial Intelligence?
AI was originally conceptualized as empowering computing machinery to
imitate human behavior and intelligence
Today AI is branch of Computer Science which aims to create systems
that can function intelligently and independently
Sources:
http://sitn.hms.harvard.edu/flash/2017/history-artificial-intelligence/
https://www.forbes.com/sites/gilpress/2016/12/30/a-very-short-history-of-artificial-intelligence-ai/#2f03c36
https://www.livescience.com/49007-history-of-artificial-intelligence.html#targetText=The%20beginnings%2
https://digitalwellbeing.org/artificial-intelligence-timeline-infographic-from-eliza-to-tay-and-beyond/
When did AI Start?
• Similar to other branches of Computer Science and Engineering, the initial concepts date back to the early Greek, Chinese and Egyptians
• However the more specific supporting concepts and popular references began around 1300AD
Ramon Lull1308
‘The Engine’of Gulliver’s
Travels - 1726
Gottfried Leibniz1666
Thomas Bayes1763
George Boole1854
Nikola Tesla1898
Tin Man in The Wizard of
Oz1939
First Humanoid Robot depicted in Metropolis -
1927
Karel Čapekintroduces the word "robot“
1920
Leonardo Torres y Quevedo - first chess
playing machine -1914
Alan TuringTuring Machine
Automatic Computing Machine
1950 – Computing Machinery and Intelligence
Proposed an ‘imitation game’ which an ‘intelligent’ machine must pass
Turing Test
Coined the term ‘Artificial Intelligence’ in 1955
Started the Dartmouth Summer Research Project on Artificial Intelligence –widely recognized as the founding event for AI
LISP – programming language of choice for AI
Started the Dartmouth Summer Research Project on Artificial Intelligence –widely recognized as the founding event for AI
With McCarthy, started the MIT CS and AI Lab
Invented the first head-mounted graphical display and first neural network learning machine SNARC
Information Processing Language - 1956
Logical Theory Machine –1956 – the first AI program
General Problem Solver –1959 – Universal Problem Solver
AI’s InceptionFathers of Artificial Intelligence – 1950s
John McCarthy Marvin MinskyHerbert A Simon &Allen Newell
Alan TuringTuring Machine
Automatic Computing Machine
1950 – Computing Machinery and Intelligence
Proposed an ‘imitation game’ which an ‘intelligent’ machine must pass
Turing Test
Coined the term ‘Artificial Intelligence’ in 1955
Started the Dartmouth Summer Research Project on Artificial Intelligence –widely recognized as the founding event for AI
LISP – programming language of choice for AI
Started the Dartmouth Summer Research Project on Artificial Intelligence –widely recognized as the founding event for AI
With McCarthy, started the MIT CS and AI Lab
Invented the first head-mounted graphical display and first neural network learning machine SNARC
Information Processing Language - 1956
Logical Theory Machine –1956 – the first AI program
General Problem Solver –1959 – Universal Problem Solver
Fathers of Artificial Intelligence
John McCarthy Marvin MinskyHerbert A Simon &Allen Newell
AI Winter
• The initial revelations of AI encountered mountains of obstacles:
• Lack of hardware with the necessary computational power
• Very optimistic projections were not met• Disagreement among early AI academics -
specifically around the theory behind neural networks
• Academic research resurged after IBM’s Deep Blue defeated grandmaster Garry Kasparov
Where is AI being used today?
Non-Industrial AI• Language Processors on phones and
other media devices• Siri and Alexa
• Content Recommendation• Facebook and Netflix
• Markey Analysis and Algorithm Trading• Finance Sector
• Analysis and Diagnosis Support Systems• Medical Sector
• Image Recognition for Self Driving Cars• Tesla
Industrial Space
• Machine Learning and Deep Learning in Machine Vision for metrology, part inspection, and part identification
• Predictive Maintenance
Why is AI not more present in industry?
Challenges:• AI is hard• Research not prioritized• Hardware not ready
Solutions:• Open source libraries for AI• Success in consumer
electronic, medical, and finance drives perception
• New powerful and affordable AI specific hardware
AI Specific HW
CPU vs GPU:
• CPUs run only a few cores which compute complex processes sequentially
• GPUs run many simple cores which allows for parallel computing across thousands of cores
Where will AI be useful for AMR?
WHERE ITERATIONS OF INPUTS AND OUTCOMES CAN BE COMBINED TO SOLVE A
COMPLEX TASK
AI IS MOST USEFUL WHERE THE UNDERLYING THEORY BEHIND HOW A PROCESS FUNCTIONS
IS COMPLEX OR AMBIGUOUS
AI for AMRs in the near term
• Advanced obstacle avoidance with Machine Vision and Object Recognition
• Improved Global Path Planning with remote sensing plus Object Recognition
• Predictive Maintenance
• Machine Learning for path planning
MiR AI Camera
MiR AI Camera provides
extra sensory input to MiR
Fleet, potentially expanding
its vision to entire buildings
Effectively creates a
communications channel
between MiR Robots and
other kinds of vehicles
Avoids obstructed narrow
paths, crowded areas or
hazardous situations,
without even driving there
Minimizes downtime and
optimizes performance
Why is AI important for AMR?
With the acceleration of specialized AI hardware and the promise of cloud computing and 5G network, AI and robotics will continue to advance
Given the rate at which new products are being developed and the synergies between autonomous vehicles and autonomous robots, new development tools will accelerate this growth
AI for AMRs in the long term
Combine the following:• All of the branches of AI• 5G network architecture - affording ultra-reliable,
low latency communication • Virtually limitless computing power with onboard
specialized HW and Cloud Computing
AI for AMRs in the long term
Robots will be able to:• Perceive their environment through the lens of
every connected sensor – in real time• Learn how to be most useful naturally through
experience (and eventually conversation)• Maintain their own hardware by predicting
failures• Consult on increasing your overall facility
efficiency
Lights Out• 24/7 Operation with limited
downtime and interventions• Robots will supplant the dull, dirty, and dangerous tasks leading to less incidents
• More robots and less humans
Safer Environment
• Given robust systems and material supply these robotics
systems could maintain independently for many years
Reduced Cost• With minimal downtime through predictive maintenance and fully optimized workflows, operation will
trend towards perfection
Maximum Efficiency
Increase in performance and capabilities for AMR leads to:
How will AI change robotics?
From inception, the goal for Artificial Intelligence has been to create human-like
machines
By combining all known technologies and given enough time this seems inevitable
Robots take learnings to real world • We are already seeing delivery robots and service industry robots
• Given enough training time and methods for handling outlier situations, this adoption will trend towards ubiquity
And then…
The End
Sources:
http://sitn.hms.harvard.edu/flash/2017/history-artificial-intelligence/
https://www.forbes.com/sites/gilpress/2016/12/30/a-very-short-history-of-artificial-intelligence-ai/#2f03c36
https://www.livescience.com/49007-history-of-artificial-intelligence.html#targetText=The%20beginnings%2
https://digitalwellbeing.org/artificial-intelligence-timeline-infographic-from-eliza-to-tay-and-beyond/
