Dr Richard Crowder of the Department of Computing and Electronic Engineering of Southampton University presented a talk on 'Termites, Bees and Robots' to the Isle of Wight branch of Cafe Scientifique on 14 Mar 2016.

1. Dr Richard Crowder
Termites, Bees and Robots

2. Presentation will address
 Overview of robot development
 What are the current developments particularly
at the Biology/Robotics interface
 Challenges
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3. What is a robot…..
I can't define a robot, but I know one when I see
one.
Joseph Engelberger
Developed the first industrial robot in the United States, the Unimate, in the 1950s.
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4. Typical view…..
Manufacturing
Enhancing LivesExploring
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5. An opposite view point
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6. Robot Timeline
 Pre 1800 human like automatons
 1801 Jacquard Looms
 1920 Capek play: Rossum’s Universal Robots
 1940 Master-Slave Systems
 1961 Unimate installed in General Motors
 1978 Introduction of the PUMA robot
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7. …..
 1997 Soujorner Rover on Mars
 1999 AIBO Dog from Sony
 2002 Roomba – cleaner from iRobot
 2004 -7 DARPA’s Grand Challenges
 2013 Google acquires a number of Robotic
companies including Boston Dynamics
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8. Early Robots
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Japanese tea
serving robot
~19th Century
Jacquard Loom

9. Why Robots
 To help humans with tasks that are:
– Dirty
– Dangerous
– Difficult
– Dull
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10. Where do you find robots
 Manufacturing: welding, painting, assemble
 Agriculture: crop spaying, harvesting
 Medicine: surgery, genome research
 Space: exploration, assemble
 Military: ordnance disposal, drones
 Personal: cars, care assistance
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11. What is intelligence
 …the ability to acquire and apply knowledge
and skills…
 Robots can:
– Sense the environment
– Apply the information and skills
– Learn
 Intelligence is in the eye of the beholder
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12. Machina Speculatrix
First reported Behaviour Based Robot
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13. Overview
 Developed in the 1950s
 Multiple autonomous agents
– Input: light sensors, contact switch
– Output: movement, head light
 Artificial life: the robots search the location for
charging batteries (i.e. food when hungry)
 Emergent behaviour
 No programming
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14. Finding “Food”
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Hutch
Path
Machina
Speculatrix

15. A Question
 How does a termite build its mound and why is
this important to robotics?
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~1cm
~8m

16. Termites
 Very large colonies >106
 Co-operative brood care
 Division of labour
 Self organisation
– Multiple interactions
– Randomness
– Positive feedback
 Recruitment and
reinforcement
– Negative feedback
 Limited number of
available specific skills
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17. Key Features
 Create spatial-temporal structures:
– Foraging trails, nest architectures, social organisation
 Existence of bifurcations when some parameters change:
– Termites move from a non-coordinated to a coordinated
phase only if their density is higher than a threshold value
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18. Communication
 Two types of communication:
– Direct – some form of contact
– Indirect – when one individual modifies the
environment and the others respond
 Stigmergy - is a mechanism of indirect coordination
between agents or actions including use of
pheromones
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19. Constructing the Royal Chamber
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Queen’s pheromone
determines size of
chamber
Soil pheromone field
that attract workers

20. Robotic System Characteristics
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Swarm Robotics
Multi-Robotics
Single Robots
Agents
Improved task execution
Improve cooperation
and interaction
Improve robustness
and scalability
Autonomies with learning
and evolutionary capabilities
Complex system
Global communication,
Small number of individuals
Local, distributed control

21. Developing Swarm Systems
 Observe a social behaviour
 Build a simple model to explain it
 Use the model of the social behaviour as a
source of inspiration for solving a practical
problem that has some similarities with the
observed social behaviour
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22. Why swarms
• The task complexity is too high for a single
robot
• The task is inherently distributed
• Building several resource-bounded robots is
much easier than having a single powerful robot
• The introduction of multiple robots increases
robustness through redundancy
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23. Characteristics of a Swarm Robot
 Robots are autonomous
 Robots are situated in the environment and can act
to modify it
 Robots’ sensing and communication capabilities
are local
 Robots do not have access to centralized control
and/or to global knowledge
 Robots cooperate to tackle a given task
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24. 24
Emergence
 An emergent property, e.g. pattern formation, from
more basic constituents
 An emergent behaviour can appear as a result of
the interaction of components of the system
 Real life example of self-organised behaviour in
humans
– Emergence of paths across grassy area, most
popular paths are reinforced

25. Swarm Robots
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Droplet,
University of Colorado
(Operates from
powered floor)
Kilobot
Harvard University
Formica
University of Southampton

26. Key features
 Mobility
– Wheels, vibrating legs
– Quad-copters
– Fish
 Sensors
– Normally quite basic,
proximity and colour
sensors are typical
 Communication
– Flashing lights and
multi-coloured LEDs are
common
– Radio systems with very
low ranges
 End effector
– Movement of material is
normally by pushing or
simple attraction
systems
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27. Swarm intelligence…..
 Swarm intelligence is an artificial intelligence
technique based around the study of collective
behaviour in decentralized, self-organized
systems
 Swarm intelligence systems are typically made
up of a population of simple agents interacting
locally with one another and with their
environment
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28. …..
 Although there is normally no centralised control
structure dictating how individual agents should
behave, local interactions between such agents
often leads to the emergence of global
behaviour.
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29. Robot foraging
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• Inspired by Bees
• What is the best approach to maximise collection
• When should we invest effort and time into
collective robot foraging
• What side effects will communication have?
• When is it NOT a good idea for robots to recruit
each other?

30. Robot-robot interference
• Physical
• Environmental
• Informational
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31. Simulation Environment
• Continuous space and
time
• 4000×4000 units
• Base in the middle with
beacon
• Deposits randomly
distributed
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32. Individualists: I-Swarm
• Random walk
• Load resource and get its energy efficiency EE
• Bring it back to the base
• Return to the deposit location
• Using odometry
• Neighbourhood search
EE > EEmin
EE ≦EEmin
EE is the energy returned, if greater than EEmin, it is beneficial to return to the original source
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33. Bee inspired recruitment: B-Swarm
• Depending on initial state a robot can:
• Be a scout looking for a deposit
• Wait in the base for a returning forager
• Can be recruited to another robot’s deposit if it has
higher EE
• Periodically make trips to the base if random walk is
unsuccessful
• Get information from successful returning foragers
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34. I-Swarm and the environment
• Best performance for 30-75
robots, 100-300 deposits
• Too many robots => physical
interference
• Too many deposits =>
environmental interference
• Too few robots or deposits =>
hard to find anything
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35. Impact of deposits characteristics
Nectar
• 100 deposits, V=2
• 10 deposit groups of 10
• 3 groups of better quality
Cargo
• 10 deposits, V=20
• Single deposit group of 10
• Uniform deposit quality
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36. Nectar and cargo
• Nectar: B-Swarms of moderate size rapidly deplete
resource groups, but find new groups hard to locate
• Cargo: Ideal for B-Swarm 36

37. Emergent traffic management
• Congestion around the base created with I-Swarm of 100 when
foraging in an environment with a lot of deposits
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38. Emergent traffic management
• B-Swarm robots forage in groups => better flow of traffic
B-SwarmI-Swarm 38

39. When to forage collectively
1. When resources are hard to find
• Initial collection time is important
• Collection of rare minerals, not picking up litter from
streets
2. When congestion near the base is a problem
• Emergent traffic management
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40. When to forage individually
1. When resources are abundant
2. When reliability of information is low
3. When it’s cheaper, as extra behaviours are not free
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41. Summary
 Overview of some of my current research into robotics
 Many challenges still exist
 Biology and Robotics have considerable ability to inform
each over
 Intelligence in robots is a significant goal, but requires
contribution from a considerable member of technologies.
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42. https://www.ted.com/talks/aimee_mullins_prosthetic_aesthetics?language=en
https://www.youtube.com/watch?v=sjAZGUcjrP8
https://youtu.be/fCML42boO8c
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