Page 206 - Introduction to Autonomous Mobile Robots

Mobile Robot Localization

Figure 5.5 191
Growth of the pose uncertainty for circular movement (r = const): Again, the uncertainty perpendic-
ular to the movement grows much faster than that in the direction of movement. Note that the main
axis of the uncertainty ellipse does not remain perpendicular to the direction of movement.

5.3 To Localize or Not to Localize: Localization-Based Navigation versus
Programmed Solutions

Figure 5.6 depicts a standard indoor environment that a mobile robot navigates. Suppose
that the mobile robot in question must deliver messages between two specific rooms in this
environment: rooms A and B. In creating a navigation system, it is clear that the mobile
robot will need sensors and a motion control system. Sensors are absolutely required to
avoid hitting moving obstacles such as humans, and some motion control system is required
so that the robot can deliberately move.
It is less evident, however, whether or not this mobile robot will require a localization
system. Localization may seem mandatory in order to successfully navigate between the
two rooms. It is through localizing on a map, after all, that the robot can hope to recover its
position and detect when it has arrived at the goal location. It is true that, at the least, the
robot must have a way of detecting the goal location. However, explicit localization with
reference to a map is not the only strategy that qualifies as a goal detector.
An alternative, espoused by the behavior-based community, suggests that, since sensors
and effectors are noisy and information-limited, one should avoid creating a geometric map
for localization. Instead, this community suggests designing sets of behaviors that together
result in the desired robot motion. Fundamentally, this approach avoids explicit reasoning
about localization and position, and thus generally avoids explicit path planning as well.