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Topics: Introduction toRobotics

CS 491/691(X)Lecture 2

Instructor: Monica Nicolescu

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Review

Definitions Robots, robotics

Robot components

Sensors, actuators, controlState, state space

Representation

Spectrum of robot control Reactive, deliberative

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Robot Control

Robot control is the means by which the sensingand action of a robot are coordinated

The infinitely many possible robot control programsall fall along a well-defined control spectrum

The spectrum ranges from reacting to deliberating

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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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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: animalsare largely reactive

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Hybrid Control :Think and act independentl y & concurrentl y!

Combination of reactive and deliberative control Reactive layer (bottom): deals with immediate reaction

Deliberative layer (top): creates plans

Middle layer: connects the two layers

Usually called three-layer systems

Major challenge: design of the middle layer Reactive and deliberative layers operate on very different

time-scales and representations (signals vs. symbols)

These layers must operate concurrently

Currently one of the two dominant control paradigms

in robotics

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Behavior- Based Control :Think the wa y you act!

An alternative to hybrid control, inspired from biology

Has the same capabilities as hybrid control:

Act reactively and deliberatively

Also built from layers

However, there is no intermediate layer

Components have a u niform representation and time-scale Behaviors : concurrent processes that take inputs from

sensors and other behaviors and send outputs to a robotsactuators or other behaviors to achieve some goals

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Behavior- Based Control :Think the wa y you act!

Thinking is performed through a network of behaviors

Utilize distributed representations

Respond in real-time are reactive

Are not stateless not merely reactive

Allow for a variety of behavior coordinationmechanisms

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F undamental Differences of Control

Time-scale: How fast do things happen? how quickly the robot has to respond to the environment,

compared to how quickly it can sense and think

Modularity: What are the components of the control s ystem? Refers to the way the control system is broken up into

modules and how they interact with each other

Representation: What does the robot keep in its brain?

The form in which information is stored or encoded in therobot

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A Brief Histor y of RoboticsRobotics grew out of the fields of control theory , cybernetics

and AI

Robotics, in the modern sense, can be considered to have

started around the time of cybernetics (1940s)Early AI had a strong impact on how it evolved (1950s-1970s),

emphasizing reasoning and abstraction, removal from direct

situatedness and embodiment

In the 1980s a new set of methods was introduced and robots

were put back into the physical world

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Control Theor y

The mathematical study of the properties of automated control systems Helps understand the fundamental concepts governing all

mechanical systems (steam engines, aeroplanes, etc.)

Feedback: measure state and take an action based on it

Thought to have originated with the ancient Greeks Time measuring devices (water clocks), water systems

Forgotten and rediscovered in Renaissance Europe Heat-regulated furnaces (Drebbel, Reaumur, Bonnemain)

Windmills

James Watts steam engine (the governor)

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F eedback Control

Definition: technique for bringing and maintaining asystem in a goal state , as the external conditionsvary

Idea: continuously feeding back the current stateand comparing it to the desired state, then adjustingthe current state to minimize the difference ( negativefeedback ). The system is said to be self-regulating

E.g.: thermostats if too hot, turn down, if too cold, turn up

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Braitenberg Vehicles

Valentino Braitenberg (1980)Thought experiments Use direct coupling between sensors and motors

Simple robots (vehicles) produce complex behaviors thatappear very animal, life-like

Excitatory connection The stronger the sensory input, the stronger the motor output

Light sensor p wheel: photophilic robot (loves the light)Inhibitory connection The stronger the sensory input, the weaker the motor output

Light sensor p wheel: photophobic robot (afraid of the light)

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Ex ample VehiclesWide range of vehicles can be designed, by changing theconnections and their strength

Vehicle 1:

One motor, one sensor

Vehicle 2:

Two motors, two sensors

Excitatory connections

Vehicle 3:

Two motors, two sensors

Inhibitory connections

Being ALIVE

FEAR and AGGRESSION

LOVE

Vehicle 1

Vehicle 2

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A rtificial Intelligence

Officially born in 1956 at Dartmouth University Marvin Minsky, John McCarthy, Herbert Simon

Intelligence in machines

Internal models of the world Search through possible solutions

Plan to solve problems

Symbolic representation of information

Hierarchical system organization

Sequential program execution

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A I and Robotics

AI influence to robotics: Knowledge and knowledge representation are central to

intelligence

Perception and action are more central to robotics

New solutions developed: behavior-based systems Planning is just a way of avoiding figuring out what to do

next (Rodney Brooks, 1987)

Distributed AI (DAI) Society of Mind (Marvin Minsky, 1986): simple, multiple

agents can generate highly complex intelligence

First robots were mostly influenced by AI (deliberative)

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Shake y

At Stanford ResearchInstitute (late 1960s)

A deliberative system

Visual navigation in avery special world

STRIPS planner

Vision and contactsensors

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Earl y A I Robots: HILARE

Late 1970sAt LAAS in Toulouse

Video, ultrasound, laser

rangefinder Was in use for almost 2decades

One of the earliesthybrid architectures

Multi-level spatialrepresentations

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Earl y Robots: CA RT/Rover

Hans Moravecs early robotsStanford Cart (1977) followedby CMU rover (1983)

Sonar and vision

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Lessons Learned

Move faster, more robustlyThink in such a way as to allow this action

New types of robot control:

Reactive, hybrid, behavior-basedControl theory Continues to thrive in numerous applications

Cybernetics Biologically inspired robot control

AI Non-physical, disembodied thinking

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Challenges

Perception

Limited, noisy sensors

Actuation

Limited capabilities of robot effectors

Thinking

Time consuming in large state spaces

Environments

Dynamic, impose fast reaction times

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Ke y Issues of Behavior- BasedControl

Situatedness Robot is entirely situated in the real world

Embodiment

Robot has a physical bodyEmergence: Intelligence from the interaction with the environment

Grounding in reality Correlation of symbols with the reality

Scalability Reaching high-level of intelligence

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E ffectors & A ctuators

Effector Any device robot that has an impact on the environment

Effectors must match a robots task

Controllers command the effectors to achieve the desired task

Actuator A robot mechanism that enables the effector to execute an action

Robot effectors are very different than biological ones

Robots: wheels, tracks, grippers

Robot actuators:

Electric motors, hydraulic, pneumatic cylinders, temperature-sensitive materials

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Passive A ctuation

Use potential energy andinteraction with the environment

E.g.: gliding (flying squirrels)

Robotics examples:

Tad McGeers passive walker Actuated by gravity

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T ypes of A ctuators

Electric motorsHydraulics

Pneumatics

Photo-reactive materialsChemically reactive materials

Thermally reactive materials

Piezoelectric materials

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DC Motors

DC (direct current) motors Convert electrical energy into mechanical energy

Small, cheap, reasonably efficient, easy to use

How do they work?

Electrical current through loops of wires mounted on a rotatingshaft

When current is flowing, loops of wire generate a magnetic field,which reacts against the magnetic fields of permanent magnets

positioned around the wire loops These magnetic fields push against one another and the

armature turns

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Readings

F. Martin: Section 4.1

M. Matari : Chapters 2, 4