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CHAPTER 7
Human Performance in Motion
Planning
I ... do not direct myself so badly. If it looks ugly on the right, I take the left ...
Have I left something unseen behind me? I go back; it is still on my road. I trace
no fixed line, either straight or crooked.
—Michel de Montaigne (1533–1592), The Essays
7.1 INTRODUCTION
It is time to admit that we will not be able to completely fulfill the promise
contained in this book’s subtitle—explain how humans plan their motion. This
would be good to do—such knowledge would help us in many areas—but we
are not in a position to do so. Today we know precious little about how human
motion decision-making works, certainly not on the level of algorithmic detail
comparable to what we know about robot motion planning. To be sure, in the
literature on psychophysical and cognitive science analysis of human motor skills
one will find speculations about the nature of human motion planning strategies.
One can even come up with experimental tests designed to elucidate such strate-
gies. The fact is, however, that the sum of this knowledge tells us only what
those human strategies might be, not what they are.
Whatever those unknown strategies that humans use to move around, we can,
however, study those strategies’ performance. By using special tests, adhering to
carefully calibrated test protocols designed to elucidate the right questions, and by
carrying out those tests on statistically significant groups of human subjects, we
can resolve how good we humans are at planning our motion. Furthermore, we
can (and will) subject robot sensor-based motion planning algorithms to the same
tests—making sure we keep the same test conditions—and make far-reaching
conclusions that can be used in the design of complex systems involving human
operators.
Clearly, the process of testing human subjects has to be very different from
the process of designing and testing robot algorithms that we undertook in prior
Sensing, Intelligence, Motion, by Vladimir J. Lumelsky
Copyright 2006 John Wiley & Sons, Inc.
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