Chapter Twelve
Robotics: The Ultimate Intelligent
Agents
Defining Robot
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“A robot is a general-purpose machine
system that, like a human, can perform a
variety of different tasks under conditions
that may not be known a priori.”
[D. Nitzan, et al., 1983 (EofAI, 1992, p. 1375)]
Historical Highlights
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400 B.C.E.: A wooden dove that flaps its wings.
1500s: Rabbi Loew’s Golem
1500s: Robots that play music
1738: de Vaucanson’s duck
1818: Shelley’s Frankenstein.
1920 R.U.R. (Rossum's Universal Robots) by Karel Čapek.
1948: Wiener’s Cybernetics
1950: Asimov’s I Robot.
1951: First teleoperated articulated arm
1956: Unimation introduces the industrial robot.
1966: Shakey, the first AI robot.
1968: 2001, A Space Odyssey introduces HAL.
1999: Sony introduces the AIBO.
2002: iRobot’s Roomba.
January, 2004: Spirit and Opportunity land on Mars.
October, 2005: Stanford’s Stanley wins DARPA Grand Challenge
2006: Self-parking automobiles.
Evaluating Robotic Potentials
•
For fully autonomous performance
approaching human capability, robots would
need to: understand speech, see, plan,
reason, represent a world model, learn.
These are truly awesome accomplishments.
Biological Foundations of Robotic
Paradigms

The ability to quantify human behavior is a
foundation for being able to emulate intelligence.
 Lorenz/Tinbergen codify the way in which an
animal acquires and organizes behavior.
 Starting from a sequence of innate behaviors (e.g.,
feeding), new behaviors can evolve (e.g., hunting
is composed of searching, stalking, chasing, etc.).
Evaluation of Lorenz/Tinbergen
•
Their model fails to provide adequate
explanation for dynamic aspects of behavior.
It reflects a “top-down” philosophy and does
not sufficiently account for perception—a
behavioral “releaser.”
Action-Perception Cycle of
Animal Behavior
•
Neisser/Gibson provide a dynamic model of
human behavior.
Agent
Acts
Modifies Actions
and
Behaviors
Interaction
With the
Environment
Perception of
World Changes
Changes
Its Perception
(new viewpoint)
Evaluation of the Biological Basis
of Robots
•
Psychologists cannot account for a
number of phenomena that need to be
resolved before transfer to mechanical
intelligent agents: concurrent behavior
conflicts, missed affordances (some
behaviors may not be described simply by
sensory-action activities), learning (not
fully resolved among cognitive scientists).
Foundations of Robotic
Paradigms
•
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A paradigm is a philosophy for working with a class of
problems.
Each of the prominent robotic paradigms includes a
series of primitive functions: sense, plan, act.
• Sense: convert elements of an environment into
information used by other parts of the system.
• Plan: elements corresponding to human reasoning
capabilities.
• Act: includes the motor and activation elements of
robotic environments.
Evaluation of Paradigm
Foundations
• The ability to learn is a biological feature
of more advanced animals. A growing
number of Roboticists believe that a new
primitive needs to be added to robotic
architectures—a learn process. There are
presently no formal organizations in which
such a process is fully integrated.
The Hierarchical Robotic
Paradigm
Includes sensors
and possible
feature extraction
SENSE
Creates a model;
develops a plan to
complete a task;
produces commands
for the actuators
Controls
actuators
PLAN
ACT
Evaluation of the Hierarchical
Paradigm
•
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PLAN reflects the way people “think” about
an action. However, not all action is
“preceded” by thinking. Humans may have a
repertoire of default schemes for completing
a task.
This model presupposes a single global
model of the world. Generic global world
models do not handle “surprises” very well.
Reactive Paradigm (also known
as Subsumption)
A fundamental behavior
SENSE
Sensor 1
ACTUATOR
Behavior 1
Behavior 2
Sensor 2
Behavior 3
Complex,
“intelligent”
behaviors—a
combination
of simple
behaviors
Evaluation of the Reactive
Paradigm
•
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Whether such architectures can be ported
(reused) to new applications is an open
question. They are not easily transferred to
domains where reasoning about resource
allocation is essential.
Lack redundancy (e.g., a second of backup
sensing system).
Assemblages of behaviors depend heavily
on the programmer.
The Hybrid Paradigm
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Designs characterized by a combination of
reactive behaviors and planning.
The PLAN component includes a deliberative
process.
Behavior includes reflexive as well as innate and
learned behaviors (skills).
Assemblages of behaviors sequenced over time,
rather than primitives.
Planning can include: path planning, map making.
Hybrids also include performance modeling.
Evaluation of Hybrid
Architectures
•
Full evaluation is difficult because Hybrid
organizations are still evolving.
• There is no currently predominant architecture;
each must be considered in light of its application.
• Are Hybrid designs really unique or merely
variations of Hierarchical architectures?
• Can suffer from limitations of computing capacity
and an associated paucity of planning intelligence.
Overall Evaluation of Robots
(Two views from the same institution)
• “The body, this mass of biomolecules, is a machine that
acts according to a set of specifiable rules . . . I believe
myself and my children all to be mere machines”
Rodney Brooks, Director of the MIT AI Laboratory
• “The reason there are no humanlike robots is not that the
very idea of a mechanical mind is misguided. It is that the
engineering problems that we humans solve as we see and
walk and plan and make it through the day are far more
challenging than landing on the moon or sequencing the
human genome. Nature, once again, has found ingenious
solutions that human engineers cannot yet duplicate.”
Steven Pinker, Director of the Center for Cognitive
Neuroscience at MIT