Page 48 - Sensing, Intelligence, Motion : How Robots and Humans Move in an Unstructured World

BASIC CONCEPTS 23

in the last three decades. For a while, some of them became “widely known
in narrow circles” of robotics engineers; today almost none of them are remem-
bered. Why so, especially given the remarkable success of computer programming
languages?
The main reason for this is, one might say, a linguistic inadequacy of such
languages to the problem of describing a motion. The product of a human oral
or written speech, or of a computer programming language, is a linear, one-
dimensional, discreet set of signals—sounds if spoken and symbols if written. A
motion, on the other hand, happens in two- or three-dimensional space and is a
continuous phenomenon. It is very difficult to describe in words, or in terms of a
computer program, a reasonably complex two- or three-dimensional curve (unless
it has a mathematical representation). Try to show your friend a motion—say, try
to wave your hand goodbye. Then ask your friend to repeat this motion; he will
likely do it quite close to your original motion. Now try to describe this same
motion on paper with words. Take your time. Once ready, give your description
to another friend, who did not see your motion, and ask him to reproduce the
motion from this description. (Writing “Please wave your hand goodbye” is, of
course, not allowed). The result will likely be far from the original.
This is undoubtedly the reason why we will never know how people danced in
ancient Egypt and Greece and Rome, and even in Europe at the end of the XIX
century, until the appearance of moving motion cameras. Unlike the millennia-
old alphabets for recording human speech, alphabets for describing motion have
been slow to come. Labanotation, the first system for recording an arbitrary (but
only human) motion, appeared only in the mid-1920s and is rather clumsy and
far from perfect.
The automatic programming technique is a further development in robot teach-
ing techniques, and it is even further removed from using real motion in teaching.
Take an example of painting the car engine compartment for a given car model.
The argument goes as follows. By the time the robot painting operation is being
designed, complete description of the car body is usually in a special database, as
a result of the prior design process. Using this database and the painting system
parameters (such as dimensions of the paint spray), a special software package
can develop a path for the painting gun, and hence for the robot that holds the
gun, such that playing that path would result in a complete and uniform paint
coverage of the engine compartment. There is no need to involve humans in the
actual motion teaching. Only a sufficiently sophisticated manufacturing environ-
ment can benefit from this system: Even with the right robot, one will have hard
time producing a database necessary to paint one’s backyard fence.
While showing an increasing sophistication from the first to the last robot
teaching techniques above, from manual guidance to automatic programming of
robot motion, each of these techniques has its advantages and its shortcomings.
For example, no other techniques can match the ingenious teaching-by-showing
ability of the first, manual guidance, method. This has led some researchers to
attempt combination techniques from the list above. For example, first a vision
system would record the human manually guided motion, and then a special