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A System based on Swarm Intelligence and Ant Foraging Techniques


A System based on Swarm Intelligence and Ant Foraging Techniques By Kristin Eicher-Elmore What is Swarm Intelligence? Swarm Intelligence is a system in which more ... – PowerPoint PPT presentation

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Title: A System based on Swarm Intelligence and Ant Foraging Techniques

A System based on Swarm Intelligence and Ant
Foraging Techniques
  • By Kristin Eicher-Elmore

What is Swarm Intelligence?
  • Swarm Intelligence is a system in which more than
    one unsophisticated agents work together to
    create a solution to difficult tasks.

Some definitions relevant to Swarm Intelligence
  • Collective behavior The process of a group of
    agents working together to achieve a common goal.
  • Reactive behavior The reaction of an agent to an
    outside stimulus such as a light.
  • Emergent Phenomena The process where new
    behaviors develop dynamically during the process
    of solving a task.

Why is using Swarm Intelligence Techniques
Important for Robotics Systems?
  • Cost Effectiveness of
  • Hardware and
  • Software

Cost Effectiveness of Hardware
  • Simple agents have inexpensive hardware that can
    be easily replaced if an agent is damaged or lost
    in a hazardous environment.
  • Inexpensive hardware leads to the ability to
    create large groups of agents that will be able
    to cover a large area.

Cost Effectiveness of Software
  • Using simple agents means that the Software must
    be kept relatively simple and uncomplicated.
    These systems generally will not have the memory
    space for complex algorithms. Thus, the reaction
    times will generally be quicker for fast reaction

Purpose of the System
  • To create a model for a system that will use
    features of the ant foraging techniques to find
    the shortest path to a goal for Search and Rescue
  • Military uses
  • Fire and disaster rescue
  • Police uses
  • Any situation where there is danger and the
    need to get to a victim quickly.

Ant Foraging Techniques
  • Ant foraging techniques were chosen because of
    the ants ability to find the shortest path to a

Ant Foraging Technique Definitions
  • Stigmergy Indirect communication used for
    communication between different insects such as
    ants. It is opposed to direct cues such as
    visual or auditory ones.
  • Pheromones The chemical scent used by ants to
    communicate with one another in an indirect way.
  • Mass recruitment The process by which ants are
    directed towards a food source through the use of
    pheromone trails.

How does Mass Recruitment work to find the
shortest path?
  • The first ant to find the food source and return
    to the nest leaves a pheromone trail for the
    other ants to follow.
  • Another ant follows this trail since it has the
    freshest and strongest scent and leaves a scent
    trail reinforcing the path.
  • The path is now established and it will be the
    shortest one because of the fact that the first
    one to return took the least time finding the

Problems with adhering strictly to ant foraging
  • Ants will meander around until they find a
    food source. When they return this path is
    usually the shortest but wandering will not work
    with a robot without ensuring that it has a good
    efficient search algorithm.

The algorithm How this system ensures a good
  • The use of colored zones.
  • Constant changing of search methods
  • Constant search for food source through each
    search iteration
  • Adequate obstacle avoidance
  • Quick and Responsive RF Communication

The use of colored zones
  • Once the robot reaches this marker the search
    method is changed to a forward search and this
    ensures that the robot will keep moving on and to
    keep the boe-bot from doubling back if it is
    making a left or right wall hug search.
  • This feature serves to force a progression
    towards the goal.

Making progress with colored zones
Constantly changing search methods
  • Changing search methods from a forward to a right
    wall hug, and a left wall hug search make sure
    that the robot will not keep trying the same
    route over and over and wander aimlessly.
  • These search methods are stored in memory to be
    communicated to the follower ants as a map.

Robot changing search methods
Constant search for the food
  • The food is searched for prior to every step
    forward the robot makes. This ensures that the
    robot will not miss it.
  • When the robot senses the food it will enter a
    separate search loop that does not involve the
    switching of search methods performed when in
    travel mode. This further ensures that the food
    will not be passed by.

Food Search
Quick Obstacle Avoidance
  • If the robot becomes stuck in a corner it will
    make a sweep of the surrounding area to find the
    farthest path from the wall closest to the robot
    that is clear for both sensors.
  • The robot also moves quickly through obstacles.

Robot becoming Unstuck in a Corner
Robot moving through Obstacle Course
Quick and Responsive RF Communication
  • Fast wireless communication means the follower
    robots can make a quick trip to the food goal.

The Scout Robot Communicating to Follower Robots
The System Algorithm Attempts to Find the
Shortest Path by
  • Using Zones to mark progress so that scouts make
    quicker progress by not becoming stuck in one
  • Using more than one search method so that the
    robot does not end up hugging one wall or
    traveling forward and going along every obstacle
    until the goal is reached.
  • Sensing for the food at a constant rate so it
    isnt passed
  • Obstacle Avoidance techniques that make sure the
    robots do not become stuck in a corner for too

Emergent Behavior Nature vs. Boe-Bot
Similarities Differences
Sensing around obstacles No pheromone decay
A follower ant will scout its own way to a food source if it becomes lost Pheromone information is used as a guide rather than a strict trail
All code is written in pBasic for a Board of
Education BS2pe chip using the Parallax Basic
Stamp Editor
  • Parallax 433 Mhz Transceiver
  • Ultrasonic Ping Sensors
  • Photo-Resistors

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The Code contains two Controller Subsets
  • Scout Search Loop
  • Follower Search Loop
  • Each robot contains the same code, but a flag
    indicates whether the robot starts out as a scout
    or a follower

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Observations and Results
  • Obstacle Avoidance
  • Getting out of corners
  • Finding the Light
  • XOR Error Checking and RF communication
  • Maze size and Progression

Obstacle Avoidance
  • The code is successful at keeping the robot away
    from both walls and moving forward for forward
    search, and hugging the right and left walls for
    forward search. The robot is always successful
    at this.
  • If the robot somehow gets very close to a wall on
    one side, the ultrasonic becomes blinded. During
    debugging it was found to record a large distance
    when it is in fact right up close to it. All of
    the sensors do this. So sometimes they get stuck
    running straight into a wall at a slight angle.

Getting out of Corners
  • Involves doing a sweep of the area and chooses
    the first direction that is away from
    obstructions on both sides of the robot in a
    direction away from the obstruction.
  • On average only two tries are required to get out
    of a corner. At most three.
  • The robot always chose the right direction.

Finding the Light
  • Very successful since sensors are checked a every
  • Once the robot senses it a separate sweep and
    search is made until the light source has been
  • Each robot has always found the light if close
    enough and situations were rare of a robot going
    by it when close unless another robot was
    blocking the light.
  • Average distance when light found was five-seven
    inches away.

XOR Error Checking and RF Communication
  • XOR checksums are calculated at both ends and
    compared before a message is accepted as correct.
  • The scout will send out a message three times
    with two seconds in between to ensure the correct
    message is received.
  • However during debugging and testing
    communication never failed after the first

Maze size and Progression
  • If the maze walls are too far apart then when the
    robots go over a colored zone or marker, they
    dont realize they are making progress. They
    might double back and think it was new ground
    they were seeing when in fact it was the same
    marker it has already seen.
  • There did not seem to be any way to solve this in
    code. The only solution seems to be keeping the
    walls from being too far apart.

Live Demonstration
Recorded Demo
Challenges and Changes
  • Communication and Error Checking
  • Hardware Changes
  • Mapping Technique Changes

Communication and Error Checking
  • At first there was more communication going on.
    Each robot, scout and follower transmitted and
    received. This was changed because of an eventual
    lack of memory space.
  • Because both scouts and followers transmitted and
    received the XOR error checking scheme was more
    exact and involved the receiver sending error
    messages to the transmitter asking for another
    transmission. Again this was simplified due to
    little memory space.

Hardware Challenges and Changes
  • All code was simplified because major hardware
    changes were needed.
  • The main challenge was a lack of memory space due
    to the needs of the transceiver.
  • An extra chip a BS2 and a bread board were added.
  • The extra chip made it necessary to consider
    building a battery pack that would hold five
    batteries since more voltage was needed. A power
    supply temporarily solved this problem.

Hardware Challenges and Changes cont.
  • One chip the BS2pe ran logic and movement, the
    BS2 ran the transceiver.
  • The biggest problem that could not be resolved
    chip to chip communication. The BS2pe would not
    stop its program execution to notice the
    interrupt from the BS2 with the transceiver.
  • The BS2pe ran at 6000 instructions per second and
    the BS2 ran at 4000 instructions per second. The
    BS2 ran at a speed too slow to interrupt the
    program execution of the BS2pe, so the code was

Mapping Techniques
  • At first actual directions were used instead of
    search techniques. This used too much memory
    space and because each robot moves differently
    due to differences in servo motors, search
    technique mapping was more efficient.

Future Improvements
  • Obstacle Avoidance and Colored Zones
  • Finding the Goal (victim)
  • Greater number of Agents and Scouts

Obstacle Avoidance and Zones
  • Obstacle Avoidance code could remain the same yet
    with more durable robots with better traction and
    the ability to deal with potholes, etc..
  • Instead of contrasting markers used to keep track
    of progress, gps devices could be used that would
    keep track of where the robot is in relation to
    its starting point and the robot could actually
    see forward progression from the starting point.

Finding the Victim
  • Instead of using light sensors, a thermal
    infrared camera could be used to identify

Greater Number of Agents and Scouts
  • A very large number of Scouts would be used to
    create better coverage of an area.
  • Once the victim was found by the quickest agent,
    RF communication with more sophisticated error
    checking could be used to bring followers
    equipped with special equipment bringing
    temporary relief like oxygen and water until
    rescuers could reach the injured.

  • A successful swarm has these components
  • Collective behavior
  • Emergent behavior
  • Reactive Behavior

Collective Behavior in this System
  • Each agent shares the goal of finding the food.
  • When one Scout finds this food, a guide is sent
    to the rest of the ants so that they can find the
    food as well.
  • All ants are cooperating together to find the

Emergent Behavior
  • Dynamic behaviors emerge during each run of the
  • A follower might find an optimal solution better
    than the guide it received from the Scout because
    it does not follow the directions blindly but as
    a hint of the right moves to make to the goal
    sensing for the light as it goes.

Emergent Behavior cont.
  • A separate search for the light source with the
    proper obstacle avoidance and sweep methods for
    the light if it has been sensed can create
    differing behaviors in each ant even if they took
    the same route enabling that no mistakes of
    missing the light can be made.
  • Changing search methods over time create possible
    changes in behavior that keep an ant from being
    stuck in a rut following one method.

Reactive Behavior
  • Apparent intelligence in insects comes from
    there reactions to their environment. Robots do
    can be made to react in similar ways with very
    simple sensors and hardware. Thus, swarm
    intelligence is an ideal way to create large and
    simple systems that can solve difficult problems
    with ease.
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