Page 18 - Sensing, Intelligence, Motion : How Robots and Humans Move in an Unstructured World

PREFACE xvii

Hence the names of approaches to motion planning in an unstructured envi-
ronment that one finds in the literature are: motion planning with incomplete
information,or sensor-based motion planning. Another good name comes from
the crucial role that this paradigm assigns to sensing: Similar to the phrase Intel-
ligence–Motion for motion planning with complete information, we will use the
name Sensing–Intelligence–Motion (SIM) for motion planning with incomplete
information. The SIM approach will help open the door for robotics into automa-
tion of unstructured tasks. (Recall “Open door, Simsim!” in the Arabian tale “Ali
Baba and the Forty Thieves.”)
The described differences in how input information appears in the Piano
Mover’s and SIM paradigms affect their approach to motion planning in cru-
cial ways—so much so that attempted symbiosis of some useful features of
“structured” and “unstructured” approaches have been so far of little theoretical
interest and little practical use.
While techniques for motion planning with complete information started in
earnest in the first years of robotics, sometime in early 1960s, the work on
SIM approaches started later, in the late 1980s, and has proceeded more slowly.
The slow pace is partly due to the fact that the field of robotics in general
and the area of motion planning in particular have been initiated primarily by
computer scientists. The combinatoric–computational professional inclinations
of these visionaries made them more enthusiastic about geometric and compu-
tational issues in robotics than about real-time control and the algorithmic role
of sensing. Another important reason is the tight connection between algorithms
and hardware that the SIM approach espouses. As we will see later, some of this
(sensing) hardware has only started appearing recently. Finally, a quick look at
this book’s table of contents will show that the work on SIM approaches requires
from its practitioners a somewhat unusual combination of background: topology,
computational complexity, control theory, and a rather strange sensing hardware.
Whatever the reasons, in spite of its great theoretical interest and an immense
practical potential, the literature on the sensor-based motion planning paradigm
is small, especially for arm manipulators. In fact, today there are no textbooks
devoted to it.
Our goals in this book are as follows:

(a) Formulate the problem of sensor-based motion planning. We want to
explore why the relevant issues are so hard—so much so that in spite
of hard work and some glorious successes of robotics, there is no robot
today that can be left to its own devices, without supervision, outdoors
or in one’s home. Build a theoretical foundation for sensor-based motion
planning strategies.
(b) Study in depth a variety of particular algorithmic strategies for mobile
robots and robot arm manipulators, and try to identify promising directions
for conquering the general problem.
(c) Given the similarity of underlying tasks and requirements, compare robot
performance and human performance in sensor-based motion planning.