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Bipin Indurkhya

Cognitive Robotics

International Institute of Information TechnologyHyderabad

Bipin Indurkhya Cognitive Robotics 2

The goal of Cognitive Robotics?

To design sociable robots!

What is a sociable robot?

A robot that can interact withpeople naturally!

Cognitive Robotics

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Why build sociable robots?• To work in a human environment (house,

hospital, museum, etc.)• To provide companionship for humans (e.g.

robot pets)• For entertainment.• To study human cognition and human social

behavior.

It is not useful to have social skills or emotions inthe factory robots, space-exploration robots, etc.


Aspects of Sociable Robots:

1. Social Interaction

• Embodiment: having a body.• Sharing an environment with the user.• Situated cognition: contextual

understanding and actions.

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2 Social intelligence• Understand human behavior in the context• Understand human emotions• Act in an intuitively understandable way• Empathy: put oneself in other person’s shoes

– The movie bladerunner• Social communication: empathy-based

understanding



3. Autonomy

• Project an illusion of life.• Display intentionality.• Convey personality.• Show unexpected behavior (sometimes!)

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Humans naturally tend to associatebeliefsgoalsperceptionsfeelingsdesires

to objects in their environment

Eliza Effect: Anthropomorphization


Eliza Program: HistoryIn late 1960s, Joseph Weizenbaum wrote asimple conversation program called Eliza.

The program used a simple keyword-basedalgorithm to carry out the conversation.

The program did not understand anything!

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A sample conversation with ElizaMen are all like.IN WHAT WAYThey’re always bugging us about something or other.CAN YOU THINK OF A SPECIFIC EXAMPLEWell, my boyfriend made me come here.YOUR BOYFRIEND MADE YOU COME HEREHe says I’m depressed much of the time.I AM SORRY TO HEAR YOU ARE DEPRESSEDIt’s true. I am unhappy.DO YOU THINK COMING HERE WILL HELP YOUNOT TO BE UNHAPPY.


A sample conversation with Eliza…I need some help, that much seems certain.WHAT WOULD IT MEAN TO YOU IF YOU GOT SOMEHELPPerhaps I could learn to get along with my mother.TELL ME MORE ABOUT YOUR FAMILY.My mother takes care of me.WHO ELSE IN YOUR FAMILY TAKES CARE OF YOUMy father.YOUR FATHERYou are like my father in some ways.WHAT RESEMBLANCE DO YOU SEE.

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A sample conversation with Eliza…You are not very aggressive but I think you don’t want me to notice that.WHAT MAKE YOU THINK I AM NOT VERY AGGRESIVEYou don’t argue with me.WHY DO YOU THINK I DON’T ARGUE WITH YOUYou are afraid of me.DOES IT PLEASE YOU TO BELIEVE I AM AFRAID OF YOUMy father is afraid of everybody.WHAT ELSE COMES TO MIND WHEN YOU THINK OF YOURFATHERBullies.DOES THAT HAVE ANYTHING TO DO WITH THE FACTTHAT YOUR BOYFRIEND MADE YOU COME HERE.


Eliza EffectEven though it was a simple program,

People spent hours conversing with it!

They told very personal things to the program

Even people who knew it was just a program,acted as if talking to a real person when

conversing with the program

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Eliza Effect: Moral 1

Weizenbaum found it very troubling thatpeople would knowingly and willingly

attach themselves emotionally to aprogram that didn’t understand

anything!

Computer power and human reason (1976)


Eliza Effect: Revival

• In the past ten years or so, a number ofrobotic systems have incorporatedEliza-like behavioral interface:– Castlemate: MIT Media Lab– Sony’s XDR-3– Primo Puel (Japan)– Paro the Seal (Japan)

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Therapeutic role of Eliza-likeBehavior

• Children/Adult feel more comfortableconfiding to a robotic agent:– Benign, non-threatening personality– User-centered– Anonymity factor– Novelty factor– Availability factor

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Therapeutic Role of Eliza-Effect

• Primo Puel dolls were originallydesigned to be a substitute boyfriendfor young single girls in the workforce.

• But were a big hit with elderly peopleacross Japan!


Eliza Effect: Moral 2You don’t need to do much to make thebehavior of a robot believable!

Such systems can sometimes be moreeffective than a human therapist!!

But we must deliberately design the robot’sbehavior to mimic human behavior.

People are naturally gullible!

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4. Understand human behavior

• Social perception:– Identification: Who is doing it– Recognition: What is he/she doing– Emotive expression: How is he/she doing it


4. Understand human behavior:Social cognition

• Understand behavior in social terms:– Stories, scripts, myths…– Symbolic models of the ‘other’– Empathy: put oneself in other person’s shoes

Empathy is considered a very human attribute.

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Aspects of Sociable Robots:5. Understand ‘self’

• Need to have a model of it’s own self:– How it’s actions and behavior will be interpreted

by humans.• Readability:

– It’s actions, behavior, and expression must give aclear feedback to the user about its internal state.

Must react in an intuitively understandable way!


Aspects of Sociable Robots:6. Socially-situated learning

• Learn from social interaction:– Direct tutoring– Observational conditioning– Goal emulation– Imitation– Others…

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6. Social learning: Imitation

• Perception: Selecting what matters• Action: Deciding which action to take• Feedback:

– Expressive: expressions of the instructor– Robot’s expression: instructor adjusts the pace– Iterative: bootstrapping

Imitation is a key learning mechanism in human!


Design issues for sociable robots

• Social environment– Benevolent environment and a friendly user

• Real-time performance– React and respond to stimulus in real time

• Appropriate social expectations– Appealing appearance encourages interaction– Appearance must be consistent with the ability:

• Infant-like robot must display infant-like expressions(Kismet, Infanoid robot at CRL, Sony’s SDR-4X…)

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Design issues for sociable robots: 2

• Self-motivated interaction– Should seem to have ‘needs’ and ‘wants’

• Regulation of interaction– Provide appropriate feedback (verbal or facial) to

the user (over-stimulated or under-stimulated)• Readable social cues

– Provide intuitive feedback of its internal state



• Interpret human social cues– Perceive and respond appropriately

• Competent behavior in a complex world– Exhibit robust, flexible, and appropriate behavior

in a complex, changing environment– Use its limited resources optimally– Show a reasonable persistency when there are

multiple conflicting goals

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• Convey intentionality• Promote empathy• Be expressive• Allow variability

Believable behavior


Advantages of Sociable Robots

• Enjoyable interaction• No special training needed for humans:

– Humans are already adept at social interaction• The user can teach the robot:

– No specialist required!

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Some cognitive robotics projects

• Infanoid robot: CRL (Kyoto/Nara)http://www2.crl.go.jp/jt/a134/xkozima/index.html

• Humanoid DB robot: ATR (Kyoto)http://www.cns.atr.co.jp/hrcn/

• Robovie project: ATR (Kyoto)http://www.irc.atr.co.jp/index.html

• SAIL/Dav project: http://www.cse.msu.edu/~weng/• COG/Kismet robot: MIT

http://www.ai.mit.edu/projects/humanoid-robotics-group/


Design of ‘Kismet’

• ‘Kismet’ is from Persian, means fate.• Three modes of interaction with the user:

– Facial expression– Tone of voice– Posture

(at the infant level!)

Design is based on the developmental psychology research!

See also the book Designing Sociable Robots by CynthiaBraezeal. The book has a CD-ROM with it that has many demo

videos.

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Developmental Psychology

• Infant’s perceptual predisposition:– Preference for human-specific visual stimuli

• Face• Eye• Mouth

– Preference for human speech

Role of social interaction in learning duringinfant-caregiver exchanges!

These preferences are preprogrammed in the robot!


Scaffolding – Bootstrapping

• Guided:– Maestro leading to a particular end

• Emergent– Open-ended: no particular goal in mind

• Internal– Incremental construction of cognitive structure

Maestro – pupil interactionController:

increasingly addscomplexity

Learner: follows themaestro

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Forms of scaffolding in infant-caregiverinteraction

• Repetition and variation– Reinforcement and introducing new behavior

• Timing and contingency– Synchronizing interactions

• Games: purposeful interactions– Goal directed– Open-ended


Design goals for Kismet

• Affective responses– Allow humans to attribute feeling to the robot

• Exploratory responses– Attribute curiosity, interest, desires, to the robot

• Protective responses– Keep robot away from harmful stimuli– Elicit caring response from humans

• Regulatory responses– Maintain an optimal environment for the robot.

To evoke the following responses from the user:

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Dynamics of robot-caregiver interaction

initiation

mutual-orientation

play-dialogue

greeting

disengagement

A Synthetic Nervous System

Wor

ld &

Car

egiv

er

sensors

motors

High-level perception system

Socialreleasers

Stimulationreleasers

People ToysLow-level

featureextraction

Motor system

orienthead &

eyes

Motor skills

face expr& bodyposture

vocalacts

Attentionsystem

Behavior system Motivationsystem

Emotionalsystem

Drives

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Overview of the Vision System

• Two wide field-of-view (fov) cameras– Mounted on the nose position– Move with the head– Direct attention to people or toys, estimate distance

• Two high resolution, narrow fov cameras– Mounted in each eye: move with the eye– Independent pan, but shared tilt– Used for post-attentional processing: eye detection


Degrees of freedom for the vision system

neck lean

neck pan

eye tilt

neck tilt

L. eye panR. eye pan

6 motors

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Degrees of freedom for the motor system

jawcontrol

eyebrowcontrol

R. earelevate

R. earrotate

L. earelevate

L. earrotate

15 motors

Total 21 motors

eyelidcontrol

lipcontrol


Low-level Visual Perception

• Highly saturate color: red, blue, green, yellow• Skin-tone color• Motion detection• Eye detection• Distance to target• Looming• Very close, excessive motion (threat)

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Attention System: Guided Search

Skin ToneFeature

Map

ColorFeature

Map

HabituationFeature

Map

MotionFeature

Map

w w w w

Frame grabber

Top downtask-driveninfluence

Eye motorcontrolAttention

reset

inhibit


Attention SystemTwo-stage processing

• Pre-attentive processing– Massively parallel (fast)– Applied over a large area– Basic visual features

• Highly saturated colors• Motion• Skin tone color

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Two-stage processingPost-attentive processing

• Localized over a small area• Applied in serial from location to location

– Determined by Attention Control• Perform more complex operations

– Eye detection– Face expression recognition– Object recognition


Pre-attentive processing

• Bottom-up or stimulus-driven• Uses data from wide fov cameras• Computes feature maps for:

– Skin tone– Color– Motion saliency

• A feature map represents activity level ateach location

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Pre-attentive processing: Top-downinfluences

• Modify the weights of the feature maps– If ‘seeking person’ then increase ‘skin tone’

weight.– If ‘avoiding toy’ then decrease ‘color’ weight

• Weights are normalized (sum is constant)• Weighted feature maps are summed up in a

single attention activation map.


Attention System: Top-down influencesstimulation

drivesocialdrive

satiatestimulation

satiatesocial

engageperson

engagetoy

avoidperson

seekperson avoid toy seek toy

attentionsystem

motivationsystem

behaviorsystem

‘person’percept

‘toy’percept

perceptualcategorization

skin &motion

color &motion satiation

strategies

suppressskin gain

intensifyskin gain

bias skingain

suppresscolor gain

intensifycolor gain

bias colorgain

Level 0

Level 1 satiationstrategies

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Attention System• Turn the gaze towards the centroid of the

most active region of the activation map• During the eye/neck movement, motion

detection processing is inhibited– To avoid the effects of self motion

• Habituation clock is reset:– To model that the interest in the same stimulus

decays with time.ω )= W・max (–1, 1 – τ

Δt

Δt: Time elapsed since the last reset


Post-attentive Processing

• Eye detection: narrow fov cameras• Proximity estimation: stereo match between

two wide fov cameras• Loom detection: Large objects that are close.

Compare the two wide fov cameras• Threat detection: Looming object + motion

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Infanoid project at CRL

• Focus on robot-humancommunication

• Model of joint-attention– Referential looking– Social referencing

• Empathy– Self-other mapping– Understanding other’s

mental state http://www2.crl.go.jp/jt/a134/xkozima/index.html


Facial Expressions of Infanoid

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Joint-attention system in Infanoid

• Identify head direction of the other person, andthen search for an object in that direction.

• Go back and forth between the person and object:referential looking

• Consider the person’s emotions towards the object:social referencing


Self-other mapping in Infanoid

• Action-based functional mapping between therobot’s body and human body (not structural)

• Incorporates neuro-physiological research on‘mirror-system’ (refer to Unit 6)

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Understanding others: empathy

• Use self-other mapping, and one’s own intentionalmodel to understand other’s intentions.

• Use this understanding to infer other’s mentalstate → this is the basis of empathy


AMD Project at MSUAutonomous

MentalDevelopment

(Michigan StateUniversity)

http://www.cse.msu.edu/~weng/

Dav on May 30, 2002

SAIL on Aug. 7, 2000

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Eight requirements for AMD• Environmental openness: Must deal with unknown and

uncontrolled environments, including various humanenvironments.

• High-dimensional sensors: Must directly deal withcontinuous raw signals from high-dimensional sensors,e.g., vision, audition and taction.

• Completeness in using sensory information. It should notdiscard, at the program design stage, sensory informationthat may be useful for some future, unknown tasks.

• Online processing: At each time instant, what the machinewill sense next depends on what the machine does now.


Eight requirements for AMD: 2• Real-time speed: The sensory/memory refreshing rate must be

high enough so that motion and speech can be temporallysampled and processed in real time (e.g., about 15Hz forvision). It must handle one-instance learning: learning fromone instance of experience.

• Incremental processing: Acquired skills must be used to assistin the acquisition of new skills, as a form of “scaffolding.” Thisrequires incremental processing.

• Perform while learning: It must perform while it “builds” itself“mentally.”

• Scale up to muddy tasks: Must handle multimodal contexts,large long-term memory and generalization, and capabilitiesfor increasing maturity, all without catastrophic memory loss.

cognitive robotics - portal.ikw.uni-osnabrueck.de file2 bipin indurkhya cognitive robotics 3 why...

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