Page 356 - Sensing, Intelligence, Motion : How Robots and Humans Move in an Unstructured World

INTRODUCTION 331

Even in simple teleoperation tasks that would be trivial for a human child,
like building a tower out of a few toy blocks or executing a collision-free motion
between a few obstacles, the result is far from perfect: Unwanted collisions do
occur, and the robot arm’s motion is far from confident. The operator will likely
move the arm maddeningly slowly and tentatively, stopping often to assess the
situation. One becomes convinced that these difficulties are not merely a result
of a (potentially improvable) inferior mechanical structure or control system, but
are instead related to cognitive difficulties on the part of the operator. This is an
exciting topic for a cognitive scientist, with important practical consequences.
To summarize, here are a few reasons for attempting a comparison between
human and robot performance in motion planning:
• Algorithm Quality. Sensor-based motion planning algorithms developed in
the preceding chapters leave a question unanswered: How good are they?
If they produced optimal solutions, they would be easy to praise. But in a
situation with limited input information the solutions are usually far from
optimal, and assessing them is difficult. One way to assess those solutions
is in comparison with human performance. After all, humans are used to
solving motion planning problems under uncertainty and therefore must be
a good benchmark.
• Improving Algorithms. If robot performance turns out to be inferior to
human performance, this fact will provide a good incentive to try to under-
stand which additional algorithmic resources could be brought to bear to
improve robot motion planning strategies.
• Synergistic Teleoperation Systems. If, on the other hand, human perfor-
mance can be inferior to robot performance—which we will observe to
be so in some motion planning tasks—this will present a serious challenge
for designers of practical teleoperation systems. It would then make sense
to shift to robots some motion planning tasks that have been hitherto the
sole responsibility of humans. We will observe that humans have difficulty
guiding arm manipulators in a crowded space, resulting in mistakes or, more
often, in a drastic reduction of the robot’s speed to accommodate human
“thinking.” Complementing human intelligence with appropriate robot intel-
ligence may become a way of dramatically improving the performance of
teleoperated systems.
• Cognitive Science. Human performance in motion planning is of much inter-
est to cognitive scientists who study human motor skills and the interface
between human sensory apparatus and motion. The performance compari-
son with robot algorithms in tasks that require motion planning might shed
light on the nature of human cognitive processes related to motion in space.
To be meaningful, a comparison between human and robot performance must
take place under exactly the same conditions. This is very important: It makes no
sense, for example, to compare the performance of a human who moves around
blindfolded with the performance of a robot that has a full use of its vision