Transcript Localization Presentation by Lucy

Exploring Different
Localization Technologies
Lucy Huh
Master’s Electrical and Computer Engineering
Outline
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Technologies Explored:
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Visual Localization
Sound Localization
Passive Infrared (PIR) Sensors
IR Remote Control
Technology Chosen:
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IR Remote Control
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IRMan
Visual Localization
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Robot will head toward the user who is
distinguished by bright clothing.
However,
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Cannot expect elders to dress differently
Cameras are expensive
Sound Localization
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Robot will head toward the user using
microphones as “ears”.
Pros:
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All-directional
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Microphone receives sound energy from all directions.
Therefore, no line-of-sight problem.
Audition requires no illumination, enabling a robot
to work in darkness or low light.
Audition is not effected by obstacles.
However, difficult to implement in given
amount of time with limited experience in
Robotics.
Passive Infrared (PIR) Sensors
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PIR Sensors are passive:
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They detect radiation but do not emit it.
They are maximally sensitive to objects that emit
heat energy at the wavelength emitted by
humans.
Robot “sees” infrared heat energy emitted by
people.
Triggering occurs when a change in infrared
levels are detected.
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When a warm object moves in or out of view of
one of the sensor’s “eyes”
PIR Sensors (continued..)
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Cons:
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Strictly line-of-sight devices
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Cannot “see” around corners or see a person if
there’s an obstruction.
Robot will not be able to distinguish
between two users in the same room.
Technology Chosen :
IR Remote Control
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Using an IR Remote control and the
CARMEN Robot Navigation Software
Toolkit for mobile robot control.
IR Remote Control done using
commercial device, IRMan.
IRMan
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IRMan can received
infrared signals by all
sorts of remotes.
Receiver can reach up
to 10m and has a 80
degree angle of sight.
On the back there is a
cable that connects to
a serial port on the PC.
Does not require any
external power.
Software for IRMan
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Wrote software to parse the serial data
from the IRMan and figure out which
button on the remote was pressed.
This software was integrated to the
wheelchair.
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Specifically, it was integrated to the
CARMEN navigation software toolkit for
mobile robot control.