Robotics 6

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    CS 491/691(X) - Lecture 1 1

    EXPERT SYSTEMS AND SOLUTIONS

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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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    CS 491/691(X) - Lecture 1 13

    An assortment of robots

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    CS 491/691(X) - Lecture 1 14

    Anthropomorphic Robots

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    CS 491/691(X) - Lecture 1 15

    Animal-like Robots

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    CS 491/691(X) - Lecture 1 16

    Humanoid Robots

    Robonaut (NASA) Sony Dream Robot

    Asimo (Honda)

    DB (ATR)

    QRIO

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    CS 491/691(X) - Lecture 1 17

    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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    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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    CS 491/691(X) - Lecture 1 20

    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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    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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    CS 491/691(X) - Lecture 1 26

    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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    CS 491/691(X) - Lecture 1 27

    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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    CS 491/691(X) - Lecture 1 29

    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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    CS 491/691(X) - Lecture 1 32

    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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    CS 491/691(X) - Lecture 1 33

    Readings

    F. Martin: Sections 1.1, 1.2.3

    M. Matari: Chapters 1, 3