Advanced Topics in Robotics

CS493/790 (X)

Lecture 1

Instructor: Monica Nicolescu

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General Information

• Instructor: Dr. Monica Nicolescu

– E-mail: monica@cs.unr.edu

– Office hours: Tuesday, Thursday; 11:00am-noon

– Room: SEM 239

• Class webpage:

– http://www.cs.unr.edu/~monica/Courses/CS493-790/

• Lectures

– Tuesday: 9:30-10:45am SEM 344

• Laboratory

– Thursday: 9:30-10:45am SEM 246

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What will we Learn?

• Cover fundamental aspects of robotics– What is a robot?

– Robot control architectures

• Advanced robotics techniques– Biologically inspired robotics

– Robot learning: reinforcement, imitation, demonstration, genetic algorithms

– Multiple robot systems: coordination and cooperation

– Human-robot interaction

– Navigation and mapping

• Hands-on experience

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Readings and Presentations

• Two papers (on average) discussed at each lecture

• Each paper is presented by a student

• Presentation guidelines

– At most 30 minutes

– Briefly summarize the paper

– Discuss the paper, its strengths, weaknesses, any points

needing clarification

– Addressing any questions the other students may have

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Readings and Paper Reports

• For each paper, all students must submit, at the

beginning of the class a brief report of the paper

• Report format (typed)

– Student's name

– Title and authors of the paper

– A short paragraph summarizing the contributions of the

paper

– A critique of the paper that addresses the strengths and

weaknesses of the paper

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Project/Lab Testbeds

• The Player-Stage-Gazebo simulator

(playerstage.sourceforge.net) – Player is a general purpose language-indepedent network

server for robot control

– Stage is a Player-compatible high-fidelity indoor multi-robot

simulation testbed

– Gazebo is a Player-compatible high-fidelity 3D outdoor

simulation testbed with dynamics

– Player/Stage/Gazebo allows for direct porting to Player-

compatible physical robots.

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Project/Lab Testbeds

• One Player-compatible ActivMedia Pioneer 3 DX – sonar sensors

– Laser

– PTZ camera

– Onboard computer

• One Player-compatible ActivMedia Pioneer 1 AT robot– 7 sonar sensors and requires the use of a laptop (not provided)

• 16 LEGO robot kits– Handy Board microcontroller

– Programming in Interactive C

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Project

• Individual project on topics covered in class

• Project topics: an implementation of either:

– a single robot system (involving complex behavior and

demonstrated on a physical robot) or

– a multi-robot system (involving cooperation/

communication/ coordination between robots and

demonstrated in simulation)

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Project Reports

• Should include the following:– Title, author

– Abstract

– Introduction and motivation

– Problem definition: project goals, assumptions, constraints, and evaluation criteria

– Details of proposed approach

– Results and objective experimental evaluation

– Review of relevant literature

– Discussion (strengths and weaknesses) and conclusion

– References

– Appendix (relevant code or algorithms)

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Class Policy

• Grading

– Paper reports: 15%

– Paper presentations: 20%

– Participation in class discussions: 15%

– Lab assignments: 20%

– Final project: 30%

• Late submissions

– No late submissions will be accepted

• Attendance

– Full participation in class discussions

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Important Dates/Milestones

• February 23

– Project topic proposal and presentation

– One page that outlines the specific goals, contribution,

implementation platform and the proposed approach

• April 6

– Project status presentations

– 5 minute in-class presentation

– One-two pages that describe the current status of the

project, what has been done, what is still to be done

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Important Dates/Milestones

• May 12

– Project final presentations 

– Project final demonstrations

– Project final reports due

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Optional Textbooks

• Basic topics– The Robotics Primer, 2001. Author: Maja Mataric'

– Available in draft form at the bookstore

• Advanced topics– Behavior-Based Robotics, 2001.

Author: Ron Arkin

– Available at the library

• Lego Robots– Robotic Explorations: An Introduction to Engineering

Through Design, 2001. Author: Fred G. Martin

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Key Concepts

• Situatedness

– Agents are strongly affected by the environment and deal

with its immediate demands (not its abstract models)

directly

• Embodiment

– Agents have bodies, are strongly constrained by those

bodies, and experience the world through those bodies,

which have a dynamic with the environment

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Key Concepts (cont.)

• Situated intelligence

– is an observed property, not necessarily internal to the

agent or to a reasoning engine; instead it results from the

dynamics of interaction of the agent and environment

– and behavior are the result of many interactions within the

system and w/ the environment, no central source or

attribution is possible

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The term “robot”

• Karel Capek’s 1921 play RUR (Rossum’s Universal

Robots)

– It is (most likely) a combination of “rabota” (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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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 robot’s actuators

• Robot = 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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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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Uncertainty

• Uncertainty is a key property of existence in the

physical world

• Physical sensors provide limited, noisy, and

inaccurate information

• Physical effectors produce limited, noisy, and

inaccurate action

• The uncertainty of physical sensors and effectors is

not well characterized, so robots have no available a priori models

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Uncertainty (cont.)

• A robot cannot accurately know the answers to the

following:

– Where am I?

– Where are my body parts, are they working, what are they

doing?

– What did I just do?

– What will happen if I do X?

– Who/what are you, where are you, what are you doing,

etc.?...

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Classical activity decomposition

• Locomotion (moving around, going places)

– factory delivery, Mars Pathfinder, lawnmowers, vacuum

cleaners...

• Manipulation (handling objects)

– factory automation, automated surgery...

• This divides robotics into two basic areas

– mobile robotics

– manipulator robotics

• … but these are merging in domains like robot pets,

robot soccer, and humanoids

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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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A Brief History of Robotics

• Robotics 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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W. Grey Walter’s Tortoise

• Machina Speculatrix” (1953)

– 1 photocell, 1 bump

sensor, 1 motor, 3 wheels,

1 battery

• Behaviors:

– seek light

– head toward moderate light

– back from bright light

– turn and push

– recharge battery

• Uses reactive control, with

behavior prioritization

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Braitenberg Vehicles• Valentino Braitenberg (1980)

• Thought experiments

– Use direct coupling between sensors and motors

– Simple robots (“vehicles”) produce complex behaviors that

appear very animal, life-like

• Excitatory connection

– The stronger the sensory input, the stronger the motor output

– Light sensor wheel: photophilic robot (loves the light)

• Inhibitory connection

– The stronger the sensory input, the weaker the motor output

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

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Example Vehicles

• Wide range of vehicles can be designed, by changing the

connections 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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Artificial 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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AI 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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Background Readings

• F. Martin: Sections 1.1, 1.2.3

• M. Matarić: Chapters 1, 3