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6 Common Sensing Techniques for Reactive Robots
diagram of sensor fashion is shown in Fig. 6.3c.
Murphy incorporated pathways for all three types of behavioral sensor
fusion as well as other deliberative forms into the Sensor Fusion Effects (SFX)
architecture. SFX will be covered in Ch. 7.

6.3 Designing a Sensor Suite

Historically, reactive robots used either inexpensive infrared (IR) or ultra-
sonic transducers to detect range. The earliest behaviors focused on basic
navigational skills such as obstacle avoidance and wall following. The per-
cept for these behaviors all involve knowing the distance to an occupied area
of space. Now with the advent of inexpensive miniature cameras and laser
range finders for consumer applications, computer vision is becoming in-
creasingly common. In agricultural and transportation applications of re-
active robots, GPS technology has become popular as well. This chapter
attempts to cover the basics of these sensing modalities, and how they are
used in mobile robots. Because the sensor market is rapidly changing, the
chapter will focus on how to design a suite of sensors for use by a robot,
rather the device details.
An artificially intelligent robot has to have some sensing in order to be con-
sidered a true AI robot. If it cannot observe the world and the effects of its
actions, it cannot react. As noted in the chapter on “Action-Oriented Percep-
tion” in Artificial Intelligence and Mobile Robots: Case Studies of Successful Robot
Systems, the design of a set of sensors for a robot begins with an assessment
of the type of information that needs to be extracted. 14 This information can
PROPRIOCEPTION be either from proprioception (measurements of movements relative to an in-
EXTEROCEPTION ternal frame of reference), exteroception (measurements of the layout of the
EXPROPRIOCEPTION environment and objects relative to the robot’s frame of reference) or expro-
prioception (measurement of the position of the robot body or parts relative
to the layout of the environment).
The Colorado School of Mines fielded an entry to the 1995 UGV compe-
tition entry discussed in Ch. 5. This provides an example of different types
of sensing for a path following robot. In 1995, the follow-path behav-
ior was expanded to track both lines of the path using a wide angle lens
on the camera. follow-path could be considered exteroceptive because it
acquired information on the environment. However, the camera for the ro-
bot was mounted on a panning mast, which was intended to turn to keep
the line in view, no matter what direction the path turned in. Therefore, the