slides set number 1.. class 478/578: general 1 1.my name is marek perkowski 2.you can call my marek,...

SLIDES SET NUMBER 1.

Class 478/578: General 11. My name is Marek Perkowski

2. You can call my Marek, or Dr. Perkowski or whatever you like.

3. This class is fun, at least for me.

4. I hope that you will have fun also.

5. We build practical robots – embedded systems

6. Class is graded based on practical achievements, a little bit similar to Capstone Project.

7. You can find all information on my webpage, find me through Google.

Class 478/578: General 21. If you are a graduate student your project is more

difficult, otherwise the same.

2. Two homeworks and Project

3. No exam.

4. Student presentations (related to homeworks or projects)

5. I expect high quality of reports (many graduate students had publications based on these reports)

6. Robots connected to Internet (demo and explanation next Thursday).

Class 478/578: grading1. Homework 1 – 10 % (evolutionary algorithms and

foraging)

2. Homework 2 – 10 % (any subset of your project)

3. Presentation – 10 %

4. Project – 70 %

5. Groups – 1 to 5 students, group leader.

6. In final report, each student has a separate part to demonstrate his/her work.

7. Each student presents a separate presentation of his work.

Class 478/578: book1. Braunl.

– You can find slides to this book on internet– Book was ordered early but it must be reprinted “on

demand”.– If you have no book, do not worry. All is in my slides.– Somebody told me that PDF of all text is also on

internet

• Slides of my class on my webpage – look for “Embedded Robotics” on my main webpage.

• To find my webpage do search on Google “Marek Perkowski”

Class 478/578: your background

1. Programming– Matlab– C– C++– Java

2. Some basic digital design and interfacing experience (only in some projects)

3. Some basic math, Boolean Algebra, probability.

4. Digital Signal Processing, Image Processing (for some projects, will be covered in debth in ECE 479 next quarter)

Class 478/578: your background review

1. Boolean functions, gates and circuits

2. Finite State Machines

3. Probabilistic State Machines

4. Grammars

5. Linked Lists

6. Arduino

Class 478/578: your background information

Please give me today the following information:

1.Your first name, last name and contact (email, phone)

2.Do you want to be on my Facebook – send me message on Facebook.

3.Programming classes you have taken.

4.Programming projects you have done.

5.Robot projects you have done. Please write more.

6.Any hardware projects you have done, like fixing a radio or a computer, building a FPGA controller etc.

7.Your background (hardware, software, art, physics, math, biology, etc)

8.Are you a graduate or undergraduate student.

9.For each of three areas: theory, programming and practical robot building, write percentages of your project’s grade (I am not sure I will be able to take this into account in every case)

10.Do you prefer to work alone or in a team for this class?

Class 478/578: your background information

Please give me today the following information:

1.Your first name, last name and contact (email, phone)

2.Do you want to be on my Facebook – send me message on Facebook.

3.Programming classes you have taken.

4.Programming projects you have done.

5.Robot projects you have done. Please write more.

6.Any hardware projects you have done, like fixing a radio or a computer, building a FPGA controller etc.

7.Your background (hardware, software, art, physics, math, biology, etc)

8.Are you a graduate or undergraduate student.

9.For each of three areas: theory, programming and practical robot building, write percentages of your project’s grade (I am not sure I will be able to take this into account in every case)

10.Do you prefer to work alone or in a team for this class?

Class 478/578: Projects and Lab

1. Meeting with Chris Clark

2. Meeting with class TA

3. Webpages with previous projects

4. Interfacing to internet

5. Lab keys (cards)

Class 478/578: Projects for this year

1. Dancing hexapods

2. Foraging hexapods

3. Robot Theatre

4. Sustainable Robot for advertising

5. Robot Guide for PSU

6. Robots controlled by iPhones, Ipads, etc.

7. Advanced theories for robotics (only for individual graduate students)

EMBEDDED EMBEDDED SYSTEMSSYSTEMS

• Textbook:• T. Bräunl Embedded Robotics, Springer

2003

Plan of class

• Week 1:– Servo programming– Evolutionary algorithms

• Week 2:– Humanoid Robots– Models of robotics

• Mapping, grammars, automata, probabilistic, Braitenberg Vehicles, natural language, logic based learning.

1.1 Definition

• Definition for: embedded system

• A combination of hardware and software which together form a component of a larger machine.

• An example of an embedded system is a microprocessor

that controls an automobile engine.

• An embedded system is designed to run on its own without human intervention, and may be required to respond to events in real time.

• Source: www.computeruser.com/resources/dictionary

Applications Applications AreasAreas

Application Areas• TV• stereo• remote control• phone / mobile phone• refrigerator• microwave• washing machine• electric tooth brush• oven / rice or bread cooker• watch• alarm clock• electronic musical instruments• electronic toys (stuffed animals,handheld toys, pinballs, etc.)• medical home equipment (e.g. bloodpressure, thermometer)• …• [PDAs?? More like standard computer system]

Consumer Products

Application Areas

• Medical Systems– pace maker, patient monitoring systems, injection systems,

intensive care units, …

• Office Equipment– printer, copier, fax, …

• Tools– multimeter, oscilloscope, line tester, GPS, …

• Banking– ATMs, statement printers, …

• Transportation – (Planes/Trains/[Automobiles] and Boats)

• radar, traffic lights, signalling systems, …

Application Areas• Automobiles

– engine management, trip computer, cruise control, immobilizer, car alarm,

– airbag, ABS, ESP, …

• Building Systems– elevator, heater, air conditioning, lighting, key

card entries, locks, alarm systems, …

• Agriculture– feeding systems, milking systems, …

• Space– satellite systems, …

Application Areas

• Facts:– 1997: The average U.S. household has over 10

embedded computers (source: www.it.dtu.dk/~jan)• 1998: 90% Embedded Systems vs. 10%

Computers– (source: Frautschi, www.caliberlearning.com)

• 2001: The Volvo S80 has 18 embedded controllers and 2 busses (source: Volvo)

AutomobilesAutomobiles

Robot Robot Metaphors Metaphors and Modelsand Models

Animatronic “Robot” or Animatronic “Robot” or devicedevice

brain effectors

Perceiving “Robot”Perceiving “Robot”

brainsensors

Reactive Robot Reactive Robot is the is the simplest behavioral robotsimplest behavioral robot

Brain is a

mapping

sensors

This is the simplest robot that satisfies the definition of a robot

effectors

Reactive Robot in environmentReactive Robot in environment

brainsensors

This is the simplest robot that satisfies the definition of a robot

effectors

ENVIRONMENT is a feedback

Braitenberg Braitenberg Vehicles and Vehicles and Quantum Quantum Automata RobotsAutomata Robots

Another Example: Another Example: Braitenberg Braitenberg Vehicles and Quantum BVVehicles and Quantum BV

Braitenberg VehiclesBraitenberg Vehicles

Braitenberg Vehicles: Braitenberg Vehicles: Homework 1 ideaHomework 1 idea

1. Can you think about other robot behaviors?

2. Can you develop software for robots with other mechanics/kinematics but the same emergent principles?

3. Design circuits for switchable behaviors: like sound that switches from shy to aggressive robot.

Emotional Robot Emotional Robot has a has a simple form of memory or statesimple form of memory or state

Brain is a

Finite State

Machine

sensors

This is the simplest robot that satisfies the definition of a robot

effectors

Behavior as an interpretation of a string

• Newton, Einstein and Bohr.

• Hello Professor

• Hello Sir

• Turn Left . Turn right.

behavior

Behavior as an interpretation of a tree

• Newton, Einstein and Bohr.

• Hello Professor

• Hello Sir

• Turn Left . Turn right.

behavior

Grammar. Derivation. Alphabets.

Our First Base Our First Base Robot Robot Architecture Architecture and Designsand Designs

Fig. 1. Learning Behaviors as Mappings fromFig. 1. Learning Behaviors as Mappings fromenvironment’s features to interaction proceduresenvironment’s features to interaction procedures

AutomaticAutomaticsoftwaresoftwareconstructionconstructionfrom examplesfrom examples

(decision tree, (decision tree, bibi--decomposition,decomposition,AshenhurstAshenhurst, DNF), DNF)

Speech frommicrophones

Image featuresfrom cameras

Sonars and othersensors

Emotions andknowledge memory

probability Verbal responsegeneration (textresponse and TTS).Stored sounds

Headmovementsand facialemotionsgeneration

Neck and shouldersmovement generation

Neck and upper body movement

generation

Robot Head Construction, 1999Robot Head Construction, 1999

Furby head with new controlFurby head with new control JonasJonas

We built and animated various kinds of humanoid heads with from 4 to 20 DOF, looking for comical and entertaining values.

High school summer camps, hobby roboticists, undergraduates

Mister ButcherMister Butcher

4 degree of freedom neck

Latex skin from Hollywood

Robot Head Construction, 2000Robot Head Construction, 2000

SkeletonSkeleton Alien

We use inexpensive servos from Hitec and Futaba, plastic, playwood and aluminum.

The robots are either PC-interfaced, use simple micro-controllers such as Basic Stamp, or are radio controlled from a PC or by the user.

AdamAdamMarvin the Crazy RobotMarvin the Crazy Robot

Technical Construction, 2001 Technical Construction, 2001 DetailsDetails

Virginia WoolfVirginia Woolf

heads equipped with microphones, USB cameras, sonars heads equipped with microphones, USB cameras, sonars and CDS light sensorsand CDS light sensors

20012001

MaxMax

Image processing and pattern recognition uses software developed at PSU, CMU and Intel (public domain software available on WWW). Software is in Visual C++, Visual Basic, Lisp and Prolog.

BUG (Big Ugly Robot)BUG (Big Ugly Robot)

20022002

Visual Feedback and Learning based on Visual Feedback and Learning based on Constructive InductionConstructive Induction

20022002Uland Wong, 17 years old

Professor Perky Professor Perky

1 dollar latex skin 1 dollar latex skin from Chinafrom China

• We compared several commercial speech systems from Microsoft, Sensory and Fonix. •Based on experiences in highly noisy environments and with a variety of speakers, we selected Fonix for both ASR and TTS for Professor Perky and Maria robots.

• We use microphone array from Andrea Electronics.

Professor Perky with automated Professor Perky with automated speech recognition (ASR) and speech recognition (ASR) and text-to-speech (TTS) capabilitiestext-to-speech (TTS) capabilities

2002, Japan

Maria, Maria, 2002/20032002/2003

20 DOF

Construction Construction details of Mariadetails of Maria

location of location of controlling controlling rodsrods

location location of head of head servosservos

location location of remote of remote servosservosCustom

designed skin

skull

Animation of eyes and eyelidsAnimation of eyes and eyelids

Cynthia, 2004, June

Currently the hands

are not moveable.

We have a separate hand design project.

Software/Hardware Architecture•Network- 10 processors, ultimately 100 processors.

•Robotics Processors. ACS 16

•Speech cards on Intel grant

•More cameras

•Tracking in all robots.

•Robotic languages – Alice and Cyc-like technologies.

Face detection localizes the person and is the first step for feature and face recognition.

Acquiring information about the human: face detection and recognition, speech recognition and sensors.

Face features recognition and visualization.

Use of Multiple-Valued (five-valued) variables Smile, Mouth_Open and Eye_Brow_Raise for facial feature and face recognition.

HAHOE KAIST ROBOT THEATRE, KOREA, SUMMER 2004

Sonbi, the Confucian Scholar Paekchong, the bad butcher

Czy znacie dobra sztuke dla teatru robotow?

Editing movementsEditing movements

Yangban the

Aristocrat and Pune

his concubine

The Narrator

The Narrator

We base all our robots on inexpensive radio-controlled servo technology.

We are familiar with latex and polyester technologies for faces

Martin Lukac and Jeff Allen wait for your help, whether you want to program, design behaviors, add muscles, improve vision, etc.

New Silicone Skins

A simplified diagram of software explaining the principle of using machine learning based on constructive induction to create new interaction modes of a human and a robot.

Probabilistic Probabilistic and Finite State and Finite State MachinesMachines

Probabilistic State Machines to describe Probabilistic State Machines to describe emotionsemotions

Happy state

Ironic state

Unhappy state

“you are beautiful”

/ ”Thanks for a compliment”

“you are blonde!”

/ ”I am not an idiot”

P=1

P=0.3

“you are blonde!”

/ Do you suggest I am an idiot?”

P=0.7

Facial Behaviors of MariaFacial Behaviors of Maria

Do I look like younger than twenty three?Maria asks:Maria asks:

“yes”

“no” “no”

0.30.7

Response:Response:

Maria smilesMaria smilesMaria frownsMaria frowns

Probabilistic Grammars for performancesProbabilistic Grammars for performances

Who?

What?

Where?

Speak ”Professor Perky”, blinks eyes twice

Speak “In the classroom”, shakes head

P=0.1

Speak “Was drinking wine”

P=0.1

P=0.3

P=0.5

Speak ”Professor Perky”

Speak ”Doctor Lee”

Speak “in some location”, smiles broadly

Speak “Was singing and dancing”

P=0.5 P=0.5

P=0.1 P=0.1

….

P=0.1

Human-controlled modes of Human-controlled modes of dialog/interactiondialog/interaction

Robot asks

Human teaches

Human commandsHuman asks

Robot performs

“Hello Maria”

“Thanks, I have a question”

“Thanks, I have a lesson”

“Thanks, I have a command”

“Lesson finished”

“Questioning finished”

“Command finished”

“Stop performance”

“Question”

Dialog and Dialog and Robot’s Robot’s KnowledgeKnowledge

Robot-Receptionist Initiated Robot-Receptionist Initiated ConversationConversation

Robot

What can I do for you?What can I do for you?

Human

Robot asksThis represents operation mode

Robot-Receptionist Initiated Robot-Receptionist Initiated ConversationConversation

Robot

What can I do for you?What can I do for you?

Human

I would like to order a I would like to order a table for twotable for two

Robot asks

Robot-Receptionist Initiated Robot-Receptionist Initiated ConversationConversation

Robot

Smoking or non-Smoking or non-smoking?smoking?

Human

Robot asks

Robot-Receptionist Initiated Robot-Receptionist Initiated ConversationConversation

Robot

Smoking or non-Smoking or non-smoking?smoking?

Human

I do not understandI do not understand

Robot asks

Robot-Receptionist Initiated Robot-Receptionist Initiated ConversationConversation

Robot

Do you want a table in a Do you want a table in a smoking or non-smoking smoking or non-smoking section of the restaurant? section of the restaurant?

Non-smoking section is Non-smoking section is near the terrace.near the terrace.

Human

Robot asks

Robot-Receptionist Initiated Robot-Receptionist Initiated ConversationConversation

Robot

Do you want a table in a Do you want a table in a smoking or non-smoking smoking or non-smoking section of the restaurant? section of the restaurant?

Non-smoking section is Non-smoking section is near the terrace.near the terrace.

Human

A table near the terrace, please

Robot asks

Human-Initiated ConversationHuman-Initiated Conversation

Robot Human

Hello Maria

Robot asks

initialization

Human-Initiated ConversationHuman-Initiated Conversation

Robot Human

Hello MariaWhat can I do for you?

Robot asks

Human-AskingHuman-Asking

Robot Human

Question

Human asksQuestionRobot asks

Human-AskingHuman-Asking

Robot Human

Question

Human asks

Yes, you ask a question.

Human-AskingHuman-Asking

Robot Human

What book wrote Lee?

Human asks

Yes, you ask a question.

Human-AskingHuman-Asking

Robot Human

What book wrote Lee?

Human asks

I have no sure information.

Human-AskingHuman-Asking

Robot Human

Try to guess.

Human asks

I have no sure information.

Human-AskingHuman-Asking

Robot Human

Try to guess.

Human asks

Lee wrote book “Flowers”.

Human-AskingHuman-Asking

Robot Human

This is not true.

Human asks

Lee wrote book “Flowers”.

Human-TeachingHuman-Teaching

Robot Human

Questioning finished

Human teaches“Questioning finished” Robot asks

Human asks

Thanks, I have a lesson

Human endsHuman endsquestioningquestioning

Human-TeachingHuman-Teaching

Robot Human

Questioning finished

Human teaches“Questioning finished” Robot asks

Human asks

Thanks, I have a lesson

Robot enters Robot enters asking modeasking mode

What can I do for you?What can I do for you?

Human-TeachingHuman-Teaching

Robot Human

Thanks, I have a lesson

Human teaches“Questioning finished” Robot asks

Human asks

Thanks, I have a lesson

Human starts Human starts teachingteaching

What can I do for you?What can I do for you?

Human-TeachingHuman-Teaching

Robot Human

Thanks, I have a lesson

Yes

Human teaches

Human-TeachingHuman-Teaching

Robot Human

I give you question-answer patternYes

Human teaches

Human-TeachingHuman-Teaching

Robot Human

Question pattern:

What book Smith wrote?Yes

Human teaches

Robot Human

Answer pattern:

Smith wrote book “Automata Theory”

Yes

Human teaches

Human-TeachingHuman-Teaching

Human-TeachingHuman-Teaching

Robot Human

Checking question:

What book wrote Smith?Yes

Human teaches

Human-TeachingHuman-Teaching

Robot Human

Checking question:

What book wrote Smith?Smith wrote book “Automata Theory”

Human teaches

Human-TeachingHuman-Teaching

Robot Human

I give you question-answer patternYes

Human teaches

Human-TeachingHuman-Teaching

Robot Human

Question pattern:

Where is room of Lee?Yes

Human teaches

Human-TeachingHuman-Teaching

Robot Human

Answer pattern:

Lee is in room 332Yes

Human teaches

Human-Checking what robot Human-Checking what robot learnedlearned

Robot Human

Lesson finished

Human asksQuestionRobot asks

Human teaches“Lesson finished”

Human-Checking what robot Human-Checking what robot learnedlearned

Robot Human

Lesson finished

Human asksQuestionRobot asks

Human teaches“Lesson finished”

What can I do for you?

Human-Checking what robot Human-Checking what robot learnedlearned

Robot Human

Question

Human asksQuestionRobot asks

Human teaches“Lesson finished”

What can I do for you?

Human-AskingHuman-Asking

Robot Human

Question

Human asksQuestionRobot asks

Human teaches“Lesson finished”

Yes, you ask a question.

Human-AskingHuman-Asking

Robot Human

What book wrote Lee?

Human asks

Yes, you ask a question.

Human-AskingHuman-Asking

Robot Human

What book wrote Lee?

Human asks

I have no sure information.

Human-AskingHuman-Asking

Robot Human

Try to guess.

Human asks

I have no sure information.

Human-AskingHuman-Asking

Robot Human

Try to guess.

Human asks

Lee wrote book “Automata Theory”

Observe that robot found similarity between Smith and Lee and generalized (incorrectly)

Behavior, Dialog and LearningBehavior, Dialog and Learning

• The dialog/behavior has the following components:

– (1) Eliza-like natural language dialogs based on pattern matching and limited parsing.

• Commercial products like Memoni, Dog.Com, Heart, Alice, and Doctor all use this technology, very successfully – for instance Alice program won the 2001 Turing competition.

– This is a “conversational” part of the robot brain, based on pattern-matching, parsing and black-board principles.

– It is also a kind of “operating system” of the robot, which supervises other subroutines.

• (2) Subroutines with logical data base and natural language parsing (CHAT).

– This is the logical part of the brain used to find connections between places, timings and all kind of logical and relational reasonings, such as answering questions about Japanese geography.

Behavior, Dialog and LearningBehavior, Dialog and Learning

• (3) Use of generalization and analogy in dialog on many levels. – Random and intentional linking of spoken language,

sound effects and facial gestures. – Use of Constructive Induction approach to help

generalization, analogy reasoning and probabilistic generations in verbal and non-verbal dialog, like learning when to smile or turn the head off the partner.

Behavior, Dialog and LearningBehavior, Dialog and Learning

• (4) Model of the robot, model of the user, scenario of the situation, history of the dialog, all used in the conversation.

• (5) Use of word spotting in speech recognition rather than single word or continuous speech recognition.

• • (6) Continuous speech recognition (Microsoft)

• (7) Avoidance of “I do not know”, “I do not understand” answers from the robot. – Our robot will have always something to say, in the worst case,

over-generalized, with not valid analogies or even nonsensical and random.

Behavior, Dialog and LearningBehavior, Dialog and Learning

Questions to students1. Present a concept of a robot with architecture based on combinational logic

mapping. Design a function from gates.

2. Present a concept of a robot with architecture based on deterministic Finite State Machine. Show a graph or table of the machine. You can also draw a flowchart.

3. Present a concept of a robot with architecture based on probabilistic Finite State Machine. Show a graph or table of the machine.

4. Present a software internet robot for natural language conversation, similar to receptionist robot from this set of slides. The robot should discuss Intelligent Robotics Laboratory, its research, faculty and students. What are the “states of robot”? What are the key-words to transit from state to state, draw a diagram.

5. Analyze four different Braitenberg Vehicles based on a robot with kinematics of a standard car. Two of them can be similar to Shy and Aggressive robots from class.

6. Analyze four different “Braitenberg-like robots” that have a head and one hand. Two of them can be similar to Shy and Aggressive robots from class

This is not a homework, just to test your knowledge. You do not have to give it to me but you may if you want.