Robots: Re-Evolving Mind
or
Mass Utility Robots this Decade,
Full Automation this Century
Hans Moravec
October 2000
Abstract
Freely-roaming robots that fetch, clean, guard and do other
chores have been an elusive fantasy for decades. Industrial mobile
robots today have a very limited market because they work only on
expensively prearranged routes. Hundredfold increases in onboard
computer power in the 1990s finally allowed research robots to map
their own routes, and prowl research building hallways and offices
daylong. Industrial applications require trouble-free months, which can
probably be achieved by replacing the 2D maps in the present research
machines with hundredfold-richer 3D versions - the author's main work.
The likely first product within three years will be a basketball-sized
camera-studded "navigation head" to be retrofitted to existing
industrial transport and cleaning machines, that lets them operate
autonomously in new locations simply designated. The follow-on
business plan anticipates a growing industrial market to support the
development of mass-market products, starting with small specialized
automatic home vacuum cleaners around 2005, followed by more capable
home utility robots able to manipulate objects as well as travel, and,
sometime after 2010, a first generation of broadly-capable "universal
robots" able to run application programs for many simple chores.
These machines will have mental power and inflexible behavior
analogous to small reptiles. Following decades will see an evolution
through mammallike learning, primatelike imagination and humanlike
abstraction. By mid-century no human task, physical or intellectual,
should be beyond effective automation.
Slides
I see a strong parallel between the evolution of robot intelligence
and the biological intelligence that preceded it. The largest nervous
systems doubled in size about every fifteen million years since the
Cambrian explosion 550 million years ago. Robot controllers double in
complexity (processing power) every year or two. They are now barely
at the lower range of vertebrate complexity, but should catch up with
us within a half century. Here are some historical and projected robotic
high points, and approximate biological analogs.
-
1950: Grey Walter tortoise
Elsie
One of eight built, with phototube eye and two vacuum
tube amplifiers driving relays that controlled steering and drive
motors. Exhibited very lively behavior, would dance near a lighted
recharging hutch until its battery ran low, then enter. Its simple
tropisms resemble bacterial "intelligence".
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1960: Hopkins Beast
(really 1961-63) Using dozens of transistors, the Johns Hopkins
University Applied Physics Lab's "Beast" wandered white hallways,
centering by sonar, until its batteries ran low. Then it would
seek black wall outlets with special photocell optics, and plug itself
in by feel with its special recharging arm. After feeding, it would
resume patrolling. Much more complex than Elsie, its
deliberate behavior can be compared to a nucleated single-cell
organism like a paramecium or amoeba.
-
1970: Stanford Cart line follower
1970: SRI Shakey blocks-world
reasoner
"Stanford Cart" line follower and SRI's "Shakey" were the first mobile
robots to be controlled by computers (large mainframes doing about a
quarter million calculations per second, linked to the vehicles by
radio). Both used television cameras to see. The Cart could follow
white lines quite reliably, Shakey could find large prismatic objects
somewhat less reliably. Their control complexity was far greater than
Elsie's or the Beast's (lines can be tracked using simple Elsie-like
techniques with ground-mounted lights and photocells, but it takes
complex adaptation and prediction to do it with ambient light from a
high vantage point), and the use of computers to control robots can be
compared to the advent of multicellular animals with nervous systems
in the Cambrian explosion, which similarly took the lid off behavioral
complexity.
-
1980: Stanford Cart 3D obstacle mapper
A million calculation per second computer and more complex program
allowed the Cart to sparsely map and negotiate obstacle courses,
taking five hours to cover 30 meters, a sluglike performance.
-
1990: 2D mapping from sonar range
Ten million computations per second and a learned sensor model
permitted quite reliable 2D mapping and navigation in real time from
sonar range measurements, a performance comparable to the tiniest
fish, or a medium insect.
-
2000: 3D mapping from stereoscopic views
(room in motion 3D)
2000: 3D maps of a complex scene and a
person
(lab in 3D)
(person in 3D)
A billion calculations a second and hundreds of megabytes of
memory allows camera-equipped robots to build almost photorealistic
dense 3D maps of their surroundings. We expect to use these
techniques in commercial robots that reliably transport or clean
floors or guard routes they map themselves, with guppylike
intelligence.
-
2005: Projected large industrial
markets for 3D-perceiving robots.
A standard "head for navigation", with task-specific application
software layer, can be retrofitted to existing transport, cleaning and
security robots, allowing them to be taught new routes by
non-specialists, and smart enough to avoid most hazards.
-
2010: Mass consumer application for 3D
perception
The first may be a small, very autonomous robot vacuum cleaner that
maps a residence, plans its own routes and schedules, keeps itself
charged and empties its dustbag when necessary into a larger
container, working for months unattended.
-
2020: Robots develop towards universal
applicability
Larger machines with manipulator arms and the ability to perform
several different tasks may follow, culminating eventually in
human-scale "universal" robots that can run application programs for
most simple chores. Their tens of billion calculation per second
lizard-scale minds would execute application programs with reptilian
inflexibility.
-
2030: Robot competence becomes comparable
to larger mammals
In the decades following the first universal robots, I expect a second
generation with mammallike brainpower and cognitive ability. They will
have a conditioned learning mechanism, and steer among alternative
paths in their application programs on the basis of past experience,
gradually adapting to their special circumstances. A third generation
will think like small primates and maintain physical, cultural and
psychological models of their world to mentally rehearse and optimize
tasks before physically performing them. A fourth, humanlike,
generation will abstract and reason from the world model.
Hans P. Moravec Biography
Hans Moravec is a pioneer in mobile robot research. After
building many hobby and science-fair robots as a child, his doctoral
work in the 1970s let the Stanford Cart, a card-table-sized,
TV-equipped robot remote controlled by a large computer, map and
negotiate obstacle courses at a ten-meter-per-hour crawl. He was a
founder of Carnegie Mellon University's Robotics Institute in 1980,
where he is now a Principal Research Scientist. There has been
developing more capable perception techniques for robots that should
allow freely-navigating utility robots to appear widely this decade,
paced by increases in computing power. He is author of "Mind
Children" (1988) and "Robot" (1999), books that examine the
implications of evolving robot intelligence.