Page 33 - Sensing, Intelligence, Motion : How Robots and Humans Move in an Unstructured World

8 MOTION PLANNING—INTRODUCTION

environment around us—but with today’s technology, don’t we have more than
enough sensor gadgetry to do the job?
The purpose of this book is to identify those difficulties, see why they are so
hard, attempt solutions, and try to identify directions that will lead us to con-
quering the general problem. A few points that will be at the center of our work
should be noted. First, we will spend much effort designing motion planning
algorithms. This being the area that humans deal with all the time, it is tempting
to try to use human strategies. Unfortunately, as often happens with attempts for
intelligent automation, asking humans how they do it is not a gratifying experi-
ence. Similar to some other tasks that humans do well (say, medical diagnostics),
we humans cannot explain well how we do it. Why did I decide to walk around a
table this way and not some other way, and how did this decision fit into my plan
to get to the door? I can hardly answer. This means that robot motion planning
strategies will not likely come from learning and analysis of human strategies.
The other side of it is, as we will see, that often humans are not as good in
motion planning as one may think.
Second, the above example with moving in the dark underlines the impor-
tance of sensing hardware. Strategies that humans and animals use to realize
safe motion in an unstructured environment are intimately tied to the sensing
machinery a species possesses. When coming from the outside into a dark room,
your movement suddenly changes from brisk and confident to slow and hesitant.
Your eyes are of no use now: Touching and listening are suddenly at the center
of the motor control chain. Your whole posture and gait change. If audio sources
disappear, your gait and behavior may change again. This points to a strong con-
nection between motion planning algorithms and sensing hardware. The same
has to be true for robots.
We will see that today’s sensing technology is far from being adequate for the
task in hand. In an unstructured environment, a trouble may come from any direc-
tion and affect any point of the robot body. Robot sensing thus has to be adequate
to protect the robot’s whole body. This calls for a special sensing hardware and
specialized sensor data processing. One side effect of this circumstance is that
algorithms and sensing hardware are to be addressed in the same book—which
is not how a typical textbook in robotics is structured. Hence we hope that a
reader knowledgeable in the theory of algorithms will be tolerant of the material
on electronics, and we also hope that a reader comfortable with electronics will
be willing to delve into algorithms.
Third, human and animals’ motion planning is tied to the individual’s kine-
matics. When bending to avoid hitting a low door opening, one invokes multiple
sequences of commands to dozens of muscles and joints, all realized in a com-
plex sequence that unfolds in real time. Someone with a different kinematics due
to an impaired leg will negotiate the same door as skillfully though perhaps very
differently. Expect the same in robots: Sensor-based motion planning algorithms
will differ depending on the robot kinematics.
Aside from raising the level of robot functional sophistication, providing a
robot with an ability to operate in an unstructured world amounts to a jump in its