Page 162 - Introduction to AI Robotics

4.4.8 4.4 Potential Fields Methodologies 145
Advantages and disadvantages
Potential field styles of architectures have many advantages. The potential
field is a continuous representation that is easy to visualize over a large re-
gion of space. As a result, it is easier for the designer to visualize the robot’s
overall behavior. It is also easy to combine fields, and languages such as C++
support making behavioral libraries. The potential fields can be parameter-
ized: their range of influence can be limited and any continuous function
can express the change in magnitude over distance (linear, exponential, etc.).
Furthermore, a two-dimensional field can usually be extended into a three-
dimensional field, and so behaviors developed for 2D will work for 3D.
Building a reactive system with potential fields is not without disadvan-
tages. The most commonly cited problem with potential fields is that mul-
tiple fields can sum to a vector with 0 magnitude; this is called the local
minima problem. Return to Fig. 4.19, the box canyon. If the robot was being
attracted to a point behind the box canyon, the attractive vector would cancel
the repulsive vector and the robot would remain stationary because all forces
would cancel out. The box canyon problem is an example of reaching a local
minima. In practice, there are many elegant solutions to this problem. One
of the earliest was to always have a motor schema producing vectors with a
small magnitude from random noise. 12 The noise in the motor schema would
serve to bump the robot off the local minima.
NAVIGATION Another solution is that of navigation templates (NaTs), as implemented
TEMPLATES by Marc Slack for JPL. The motivation is that the local minima problem
most often arises because of interactions between the avoid behavior’s re-
pulsive field and other behaviors, such as move-to-goal’s attractive field. The
minima problem would go away if the avoid potential field was somehow
smarter. In NaTs, the avoid behavior receives as input the vector summed
from the other behaviors. This vector represents the direction the robot would
go if there were no obstacles nearby. For the purposes of this book, this will
be referred to as the strategic vector the robot wants to go. If the robot has a
strategic vector, that vector gives a clue as to whether an obstacle should be
passed on the right or the left. For example, if the robot is crossing a bridge
(see Fig. 4.27), it will want to pass to the left of obstacles on its right in order
to stay in the middle. Note that the strategic vector defines what is left and
what is right.
NaTs implement this simple heuristic in the potential field for RUNAWAY,
promoting it to a true AVOID. The repulsion field is now supplemented with
a tangential orbit field. The direction of the orbit (clockwise or counter-