The Best of Creative Computing Volume 2 (published 1977)

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The Thinking Computer (Robots, Applications)

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your bar-mitzvah, then you can be pretty sure that every small flat box contains
another pen-and-pencil set. If you don't come to any such quick conclusion, you
might examine the mysterious package more closely, look at the tag or postmark,
lift it to feel its weight, shake it to see if it rattles or sloshes, and you
usually will have a pretty good chance of perceiving what's inside without ever
seeing it. Similarly, it is unfair to expect a computer to recognize real
objects unless it first knows something about the expected characteristics of
the objects, such as their size, shape, color, and the normal physical
relationships among them.

Many of the past computer-vision projects tried to "simplify" their tasks by
aiming their TV cameras only at artificial objects like boxes and wedges, which
had straight-line edges and clear mathematical descriptions. Unfortunately, such
objects have objects have few expected sizes or shapes, no normal physical
relationships, and rarely any context to guide the recognition process. Because
of this, paradoxically, the attempt to simplify may actually have made the
recognition problem more difficult.

Current research is turning to more natural pictures that may incorporate curved
objects and complex surroundings. "Scene understanding systems" are now being
built that coordinate the use of several kinds and sources of knowledge in order
to solve complex problems. For example, knowledge of illumination, distance
measurements, color, spatial relationships, and physical constraints, can all
contribute to the accuracy of the interpretation of visual data.


I am not going to define the word "robot" here, because of the wide range of
interpretations it has. The following examples indicate the general kinds of
devices that we shall consider. Without getting enmeshed in the technical
details of how they work, let's look at what some of these systems were capable
of doing a few years ago.

At Hitachi Central Research Laboratory a TV camera was aimed at an engineering
plan drawing of a structure built out of various-shaped blocks. A second camera
looked at the blocks themselves, which were spread out on a table. The computer
"understood" the drawing, reached towards the blocks with its arm, and built the

At MIT, the camera was not shown a plan; instead, it was shown an example of the
actual structure desired. The computer figured out how the structure could be
constructed, and then built an exact copy.

At Stanford University, the hand obeyed spoken directions. For example, if
someone said into the microphone, "Pick up the small block on the left," that is
precisely what the arm would do.

At the University of Edinburgh, a jumble of parts for two wooden toys was placed
on the movable table near the camera. "Freddy," the Edinburgh hand-eye-table
robot system, carefully spread out the parts so that it could see each one
clearly, and then, with the help of a vise-like work station at one corner of
the table, assembled first the toy car and then the toy boat.

At SRI, Shakey the mobile robot was told to "PUSH THE BOX OFF THE PLATFORM."
Shakey had no arm, and realized that he could not reach the box unless he was on
the platform with it. He looked around, found a ramp, pushed the ramp up against
the platform, rolled up the ramp, and then pushed the box onto the floor.

Recently, robot researchers have been concentrating their efforts upon specific
technical problems that must be solved in order to create more powerful robot
systems. Major developments coming out of current work include: (1) new hardware
technology that is leading to more reliable and less expensive sensors,
effectors, and computers; (2)
new software technology, in the form of high-level programming 


tools and studies of how to structure the large knowledge bases that are
essential for any intelligent system; and (3) prototypes of simple robot systems
that can at least begin to perform truly practical tasks. For example: 

At Stanford the hand-eye system that used to stack toy blocks can now assemble a
real water pump.

At SRI a computer-controlled Unimate industrial manipulator arm with touch and
force sensors can feel its way as it packs assembled pumps into a case.

At MIT programs are under development to enable a computer to inspect and repair
circuit boards for use in computers, TV sets, and other electronic equipment.


As computers become less expensive and more widely available, society is
becoming more dependent upon them to perform conventional bookkeeping functions.
More important, however, is that as computers become more intelligent they can
take on valuable new roles in the service of society. In education, computers
constitute a rich new medium for a student's creative expression and
experimentation. They can be used to demonstrate laws of physics on a dynamic
display screen, to illustrate mathematical principles through the design of
algorithms, and to carry on tutorial conversations. In psychology, computer
models of mental behavior provide knowledge of how the mind works. In medicine,
computers can model physiological and biochemical processes, and both store and
deduce large numbers of facts about diseases, drugs, and treatments. In
industry, computers can help both in the front office, scheduling activities and
monitoring progress, and on the factory floor, directing automatic inspection,
materials handling, and assembly systems. Such activities can both increase
productivity and improve the quality of the goods produced. In mathematics and
science, computers are beginning to function as intelligent assistants to
professional scientists, performing such jobs as solving and simplifying
symbolic equations, analyzing chemical compounds, and verifying the correctness
of simple computer programs. As novel sources of information, amusement, or
artistic experiences, the potential for us to benefit from thinking computers is
limited only by our imaginations.

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