Page 209 - Introduction to Autonomous Mobile Robots

Chapter 5
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• The map, if created by the robot, can be used by humans as well, achieving two uses.
The map-based approach will require more up-front development effort to create a nav-
igating mobile robot. The hope is that the development effort results in an architecture that
can successfully map and navigate a variety of environments, thereby amortizing the up-
front design cost over time.
Of course the key risk of the map-based approach is that an internal representation,
rather than the real world itself, is being constructed and trusted by the robot. If that model
diverges from reality (i.e., if the map is wrong), then the robot’s behavior may be undesir-
able, even if the raw sensor values of the robot are only transiently incorrect.
In the remainder of this chapter, we focus on a discussion of map-based approaches and,
specifically, the localization component of these techniques. These approaches are partic-
ularly appropriate for study given their significant recent successes in enabling mobile
robots to navigate a variety of environments, from academic research buildings, to factory
floors, and to museums around the world.

5.4 Belief Representation

The fundamental issue that differentiates various map-based localization systems is the
issue of representation. There are two specific concepts that the robot must represent, and
each has its own unique possible solutions. The robot must have a representation (a model)
of the environment, or a map. What aspects of the environment are contained in this map?
At what level of fidelity does the map represent the environment? These are the design
questions for map representation.
The robot must also have a representation of its belief regarding its position on the map.
Does the robot identify a single unique position as its current position, or does it describe
its position in terms of a set of possible positions? If multiple possible positions are
expressed in a single belief, how are those multiple positions ranked, if at all? These are the
design questions for belief representation.
Decisions along these two design axes can result in varying levels of architectural com-
plexity, computational complexity, and overall localization accuracy. We begin by discuss-
ing belief representation. The first major branch in a taxonomy of belief representation
systems differentiates between single-hypothesis and multiple-hypothesis belief systems.
The former covers solutions in which the robot postulates its unique position, whereas the
latter enables a mobile robot to describe the degree to which it is uncertain about its posi-
tion. A sampling of different belief and map representations is shown in figure 5.9.

5.4.1 Single-hypothesis belief
The single-hypothesis belief representation is the most direct possible postulation of mobile
robot position. Given some environmental map, the robot’s belief about position is