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Transcript of Robotics 6
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CS 491/691(X) - Lecture 1 1
EXPERT SYSTEMS AND SOLUTIONS
Email: [email protected]
Cell: 9952749533www.researchprojects.info
PAIYANOOR, OMR, CHENNAI
Call For Research Projects Final
year students of B.E in EEE, ECE, EI,
M.E (Power Systems), M.E (Applied
Electronics), M.E (Power Electronics)
Ph.D Electrical and Electronics.
Students can assemble their hardware in our
Research labs. Experts will be guiding theprojects.
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Topics: Introduction toRobotics
CS 491/691(X)
Lecture 1
Instructor: Monica Nicolescu
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CS 491/691(X) - Lecture 1 3
General Information
Instructor: Dr. Monica Nicolescu
E-mail: [email protected]
Office hours: Tuesday, Thursday 10:30am-12:00pm
Room: SEM 239
Class webpage:
http://www.cs.unr.edu/~monica/Courses/CS491-691/
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CS 491/691(X) - Lecture 1 4
Time and Place
Lectures
Tuesday: 1:00pm-2:15pm, SFB 103
Labs
Thursday: 1:00pm-2:15pm, SEM 342A The use of the lab equipment requires a $50 deposit paid
at the cashiers office
Deposit is returned at the end of the semester
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CS 491/691(X) - Lecture 1 5
Class Policy
Grading Homeworks: 20%
Exam (1): 20%
Exam (2): 20%
Laboratory sessions: 20% Final project: 20%
Late submissions
No late submissions will be accepted
Attendance Exams, laboratory sessions and final competition are mandatory
If you cannot attend you must discuss with the instructor in
advance
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CS 491/691(X) - Lecture 1 6
Textbooks
Lectures
The Robotics Primer, 2001. Author: Maja
Mataric'
Available in draft form at the bookstore
Labs
Robotic Explorations: An Introduction to
Engineering Through Design, 2001. Author:Fred G. Martin
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CS 491/691(X) - Lecture 1 7
What will we Learn?
Fundamental aspects of robotics
What is a robot?
What are robots composed of?
How do we control/program robots? Hands-on experience
Build robots using LEGO parts
Control robots using Interactive C and the
HandyBoard microcontroller
Contests during the semester, final
competition
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CS 491/691(X) - Lecture 1 8
The term robot
Karel Capeks 1921 play RUR (Rossums Universal
Robots)
It is (most likely) a combination ofrabota (obligatory
work) and robotnik (serf)
Most real-world robots today do perform such
obligatory work in highly controlled environments
Factory automation (car assembly)
But that is not what robotics research about; the
trends and the future look much more interesting
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CS 491/691(X) - Lecture 1 9
What is a Robot?
In the past
A clever mechanical device automaton
Robotics Industry Association, 1985
A re-programmable, multi-functional manipulator designedto move material, parts, tools, or specialized devices []
for the performance of various tasks
What does this definition missing?
Notions of thought, reasoning, problem solving, emotion,
consciousness
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CS 491/691(X) - Lecture 1 10
A Robot is
a machine able to extract information from itsenvironment and use knowledge about its world to
act safely in a meaningful and purposeful manner
(Ron Arkin, 1998)
an autonomous system which exists in the
physical world, can sense its environment and can
act on it to achieve some goals
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CS 491/691(X) - Lecture 1 11
What is Robotics?
Robotics is the study of robots, autonomous
embodied systems interacting with the physical
world
Robotics addresses perception, interaction and
action, in the physical world
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CS 491/691(X) - Lecture 1 12
Robots: Alternative Terms
UAV
unmanned aerial vehicle
UGV (rover)
unmanned ground vehicle
UUV
unmanned undersea vehicle
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An assortment of robots
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Anthropomorphic Robots
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Animal-like Robots
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Humanoid Robots
Robonaut (NASA) Sony Dream Robot
Asimo (Honda)
DB (ATR)
QRIO
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What is in a Robot?
Sensors
Effectors and actuators
Used for locomotion and manipulation
Controllers for the above systems
Coordinating information from sensors with commands for
the robots actuators
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CS 491/691(X) - Lecture 1 18
Sensors
Sensor = physical device that provides informationabout the world
Process is called sensing orperception
What does a robot need to sense? Depends on the task it has to do
Sensor (perceptual) space
All possible values of sensor readings
One needs to see the world through the robots eyes
Grows quickly as you add more sensors
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CS 491/691(X) - Lecture 1 19
State
State: A description of the robot (of a system in general)
For a robot state can be:
Observable: the robot knows its state entirely
Partially observable: the robot only knows a part of its state
Hidden (unobservable): the robot does not have any access
to its state
Discrete: up, down, blue, red
Continuous: 2.34 mph
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Types of State
External The state of the world as perceived by the robot
Perceived through sensors
E.g.: sunny, cold
Internal
The state of the robot as it can perceive it
Perceived through internal sensors, monitoring (stored,
remembered state)
E.g.: Low battery, velocity
The robots state is the combination of its internal
and external state
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CS 491/691(X) - Lecture 1 21
State Space
All possible states a robot could be in E.g.: light switch has two states, ON, OFF; light switch with
dimmer has continuous state (possibly infinitely many
states)
Different than the sensor/perceptual space!!
Internal state may be used to store information about the
world (maps, location of food, etc.)
How intelligent a robot appears is stronglydependent on how much and how fast it can sense
its environment and about itself
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CS 491/691(X) - Lecture 1 22
Representation
Internal state that stores information about the worldis called a representation orinternal model
Self: stored proprioception, goals, intentions, plans
Environment: maps
Objects, people, other robots
Task: what needs to be done, when, in what order
Representations and models influence determine
the complexity of a robots brain
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CS 491/691(X) - Lecture 1 23
Action
Effectors: devices of the robot that have impact onthe environment (legs, wings robotic legs,
propeller)
Actuators: mechanisms that allow the effectors to
do their work (muscles motors)
Robotic actuators are used for
locomotion (moving around, going places)
manipulation (handling objects) This divides robotics into two basic areas
Mobile robotics
Manipulator robotics
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Autonomy
Autonomy is the ability to make ones own decisionsand act on them.
For robots: take the appropriate action on a given situation
Autonomy can be complete (R2D2) orpartial(teleoperated robots)
Controllers enable robots to be autonomous
Play the role of the brain and nervous system in animals
Typically more than one controller, each process
information from sensors and decide what actions to take
Challenge in robotics: how do all these controllers
coordinate with each other?
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Languages for Programming Robots
What is the best robot programming language? There is no best language
In general, use the language that
Is best suited for the task Comes with the hardware
You are used to
General purpose:
JAVA, C
Specially designed:
the Behavior Language, the Subsumption Language
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Spectrum of robot control
From Behavior-Based Robotics by R. Arkin, MIT Press, 1998
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Robot control approaches
Reactive Control
Dont think, (re)act.
Deliberative (Planner-based) Control
Think hard, act later.
Hybrid Control
Think and act separately & concurrently.
Behavior-Based Control (BBC)
Think the way you act.
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Thinking vs. Acting
Thinking/Deliberating slow, speed decreases with complexity
involves planning (looking into the future) to avoid bad
solutions
thinking too long may be dangerous
requires (a lot of) accurate information
flexible for increasing complexity
Acting/Reaction
fast, regardless of complexity
innate/built-in or learned (from looking into the past)
limited flexibility for increasing complexity
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How to Choose a ControlArchitecture?
For any robot, task, or environment consider: Is there a lot of sensor noise?
Does the environment change or is static?
Can the robot sense all that it needs?
How quickly should the robot sense or act?
Should the robot remember the past to get the job done?
Should the robot look ahead to get the job done?
Does the robot need to improve its behavior and be able tolearn new things?
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Reactive Control:Dont think, react!
Technique for tightly coupling perception and action to providefast responses to changing, unstructured environments
Collection of stimulus-response rules
Limitations
No/minimal state
No memory
No internal representations
of the world
Unable to plan ahead
Unable to learn
Advantages
Very fast and reactive
Powerful method: animals
are largely reactive
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Deliberative Control:Think hard, then act!
In DC the robot uses all the available sensory information andstored internal knowledge to create a plan of action: sensep
planp act (SPA) paradigm
Limitations
Planning requires search through potentially all possible plans
these take a long time
Requires a world model, which may become outdated
Too slow for real-time response
Advantages
Capable of learning and prediction
Finds strategic solutions
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Readings
F. Martin: Sections 1.1, 1.2.3
M. Matari: Chapters 1, 3