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cating that no object was sensed and 1 indicating that an object is
present. These values will be stored in the variable object_detect.
When the program execution is returned back to the main pro-
gram, certain decisions can easily be made, based on this infor-
mation.
The infrared subroutine takes 40 samples from the module and
counts the number of positive hits received. The number of sam-
ples taken can also be configured by changing the variable
num_samples. Because of stray infrared and signals from the
environment, the module is constantly producing false positive
signals that are referred to as “noise.” The average acceptable
amount of noise picked up by the sensor module is called the noise
floor. The routine needs to set a threshold point above the typical
amount of noise and report a sensed object only if the number of
positive signals received throughout the number of samples taken
exceeds the noise floor.

With the PNA4602M sensor modules, I found that the typical false
positive was actually very low—five for every 40 samples taken. To
be on the safe side, the threshold is set at 25 for every 40 samples,
to ensure that an object is present. By changing the threshold
value, you can change the sensitivity and distance detection
response of the module. If you want a more accurate reading, the
num_samples value can be increased, but will take more time for
the routine to execute.
The last option is using the mode select push button to invoke the
infrared sensor calibration routine. This will enable the user to
simply push the button on the robot’s head to calibrate the sensor,
as described earlier. The experimenter can also develop a software
routine to use the push button to choose different modes of behav-
ior when the robot starts up. When the main software routine
senses that the button has been pushed, it goes into a tight loop
until it senses that the switch has been let up before going to the

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