Page 222 - Introduction to AI Robotics

platform. The power needed to move the robot is called the locomotion load.
LOCOMOTION LOAD 6.3 Designing a Sensor Suite 205
Unfortunately, many robot manufacturers focus on only the locomotion load,
balancing power needs with the desire to reduce the overall weight and size.
This leads to a very small hotel load, and often prevents many sensors from
being added to platform.
5. Hardware reliability. Sensors often have physical limitations on how
well they work. For example, Polaroid sonars will produce incorrect range
reading when the voltage drops below 12V. Other sensors have temperature
and moisture constraints which must be considered.
6. Size. The size and weight of a sensor does affect the overall design. A
microrover on the order of a shoebox will not have the power to transport
a large camera or camcorder, but it may be able to use a miniature “Quick-
Cam” type of camera.
The above list concentrated on considerations for the physical aspects of
the sensor. However, the sensors only provide observations; without the soft-
ware perceptual schemas, the behaviors cannot use the sensors. Therefore,
the software that will process the information from a sensor must be consid-
ered as part of the sensor seletion process. 7. Computational complexity.
Computational complexity is the estimate of how many operations an algo-
rithm or program performs. It is often written as a function O, called the
“order,” where O(x) means the number of operations is proportional to x. x
is often a function itself. Lower orders are better. An algorithm that executes
2
with O(n) equally consuming operations is faster than one with O(n ) oper-
ations. (If you doubt this, see if you can find a positive, whole number value
2
of n such that n > n .) Computational complexity has become less critical
for larger robots, with the rapid advances in processors and miniaturization
of components. However, it remains a serious problem for smaller vehicles.
8. Interpretation reliability. The designer should consider how reliable
the sensor will be for the ecological conditions and for interpretation. The
robot will often have no way of determining when a sensor is providing
incorrect information. As a result the robot may “hallucinate” (think it is
seeing things that are not there) and do the wrong thing. Many sensors pro-
duce output which are hard for human to interpret without years of training;
medical X-rays are one example, and synthetic aperature radar (SAR) which
produces polar plots is another. If a sensor algorithm was not working prop-
erly in these modalities, the designer might not be skilled enough to notice
it. Therefore, the algorithms themselves must be reliable.