Learning Roomba
Module 5 - Localization
Outline
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What is Localization?
Why is Localization important?
Why is Localization hard?
Some Approaches
Using the Fixed-Camera Localization
Exercises
What is Localization?
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Process of determining where a robot is in its
environment
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Absolute position in the world
Position in a map
Relative to the start position
Relative to some landmark
Relative to another robot
Some other way of identifying location
What is Localization?
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Can be done with or without a map of the
environment
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A map contains information about the
environment that the robot can use to help
localize itself
Why is Localization important?
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Robot needs to know where it is to know how
to act
Without knowing where you are, you can only
wander around randomly
Cannot navigate to a location without
knowing where you are
Many tasks rely on navigation
Why is Localization Hard?
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Robot needs to know about its enviornment
Sensors are not always accurate
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Noisy
Unreliable
Sensors do not tell the Robot what it needs to
know
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Many sensors report distance to an object, not
where the Robot is
Some Approaches
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Odometry
Global Positioning Systems
Landmarks
Trilateration
Distance Sensors
Others
Using the Fixed-Camera
Localization
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getLocalizedX()
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Returns the Localized X-position of the Roomba
in Meters
getLocalizedY()
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Returns the Localized Y-position of the Roomba in
Meters
Using the Fixed-Camera
Localization
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X and Y positions are grid locations in the
world
Diagram taken from BBC’s website
Principles of the Fixed-Camera
Localization
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Merges 3 Concepts
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Odometry Readings
Topological Map
Image Tracking
Principles of the Fixed-Camera
Localization
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Odometry Readings
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Recorded from the sensors on the Roomba’s
wheels
Map can be built over time of where the Roomba
has visited.
Only as accurate as the sensors
Accuracy worsens over time due to drift and
skidding
Principles of the Fixed-Camera
Localization
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Topological Map
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Type of Graph
Vertices are interesting
features in the environment
Edges are transitions
between the features
Usually able to determine
when an already visited
feature has been reached
Principles of the Fixed-Camera
Localization
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Image Tracking
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Able to find the Roomba in an image
Looks for an area with an average color similar
to the average color of the Roomba
Tracked points in the image become points of
interest (Vertices) in the Topological map
Camera does not move, so the same pixel
represents the same location of the Roomba
Principles of the Fixed-Camera
Localization
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As the Roomba drives in the Environment, the
algorithm builds the Topological Map
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Vertices are tracked image coordinates
Edges are odometry readings to get from one image
coordinate to another
The Topological Map can be used to determine
the position of the Roomba
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Finds the current image coordinates where the Roomba
is
Find the shortest path between the start position and
the current position through the Topological Map
Exercises
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Report the position of a virtual wall beam. To
do so, have the robot drive until it detects a
virtual wall. Print the localized positions once
it has reached the beam.
Exercises
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Write a program that
will have the Roomba
drive in a square 10
times with each side
of the square being 1
meter long. Print out
the X-Position and YPosition according to
Odometry and
localization
Questions?