sociable machines

Sociable Machines

Cynthia BreazealMIT Media Lab

Robotic Presence Group

Cynthia Breazeal, MIT Media Lab

Human-Robot Relations

Honda’s Asimo Sony’s Aibo iRobot

Types of relationships Face to face with a robot creature Embodied, distal interactions through a robot avatar Augmented physicality through robotic extensions

Capable machines, untrained users, human environment Balance human strengths with machine capabilities Useful and enjoyable!

Robotic extensions


Robots in your everyday life

Competence in: Human engineered environment Human social environment

Untrained users of different Age, gender, culture, etc.

Human centered design Appropriate mental model Supports what comes naturally

On the job learning Easy to teach

Long-term relationships Acceptance, trust


Sociable anthropomorphic robots

Very complex technology Social interface is (Reeves&Nass)

Intuitive, natural Untrained users

Humanoid robots are well suited to this hypothesis Same morphology, sensing Share social, communication cues

HRI meets HCI Study how people want to and do

interact with them. Informs design Evaluation methods


Three research themes

HCISCIENCE

ROBOTICS & AI

Evaluate robot compatibility with people

Informed byscientific

understandingof humans

And animals

Build robots that do real thingsIn the real world with real people


Issues for sociable robots today

The real-world is Complex Ever-changing

Robots have limited abilities compared to people Motor skills Perceptual abilities Mental abilities

Imbalance in social sophistication

Yet, social interaction is Tightly coupled Mutually regulated


Early exploration into sociable humanoids

Set appropriate expectations Not human Robo-baby

Use of expressive feedback to regulate interaction Emotive expressions Communicative displays Paralinguistic cues

Use science of natural behavior as a guide

Start “simple” and learn, develop

Kismet, MIT AI Lab


Socially situated learning: A path to more capable machines?

Issues for learning systems (robots or otherwise) Knowing what matters Knowing what action to try Evaluating actions Correcting errors Recognize success Structuring learning

If task is pre-specified, then can do at design-time If not the case, then what?

Address issues through structured social interactions Robots in a benevolent learning environment


Learning from the way we teach


Social skills that support learning

Direct visual attention Indicates saliency (i.e.what matters) Match to human – find similar things

interesting Robot responds to attention directing cues of

people Robot sends feedback to person for focus of

attention


Video of attention system


Recognize communicated reinforcement Serves as progress estimator Serves as signal for goal attainment Robot should recognize affective feedback from

human Robot signal to human that intent was properly

understood



Video of communicated affect


Communicate internal state to human Allows human to:

Predict and understand robot’s behavior Tune own behavior to robot Improves quality of interaction

Robot conveys internal state to human in an intuitive manner

Can be used by both to establish better quality instruction



Communication of internal state


Regulating the interaction Provides structure to the interaction

Interactive games Variations on a theme

Avoid being overwhelmed or under-stimulated Turn-taking as cornerstone

Human interaction Human instruction



Video of proto-conversations


Lessons from Kismet

Face to face In human terms

Human drive to animate, anthropomorphize Importance of gaze Social qualities Emotive qualities Physical interaction

Being and Feeling in communication Expressive feedback is vital Entrainment and accommodation Mutual regulation

Being engaged vs. interacting


Related, ongoing directions

HRI &DESIGN

SCIENCE

ENGINEERING

Smart Puzzle Fruit HRI gaze studies

Sensate Silicone SkinOrganic Robots

Sociable robots


Sociable RobotsStan Winston Studios – Media Lab collaboration

Next generation sociable robot Fully embodied Organic look and feel Highly expressive Socially situated learning


Robot Avatars/PerformersStan Winston Studios – Media Lab collaboration

Symbiotic control Puppeteer and “single-mind”

performance Human provides content, new interfaces Robot local intelligence to perform

content

Physical medium for embodied interactions Visual, auditory, tactile Mobile Shared environment, reference frame Physical interactions with world and

others


Organic Robots

What gives a machine a living presence?

Organic qualities to make them familiar yet distinct Intriguing blend between plant and animal Silicone skin instead of plastic shells Natural and expressive movement, serpentine Visual perception of people (faces, movement, color)


Sensate Synthetic Skin“…Perhaps next to the brain, the skin is the most important of all our organ systems.” Ashley Montagu, Touching: The Human Significance of the Skin, 1986, p.4

Sensate skin for environmental interactions Active perception of material characteristics (hard, soft) Development of novel conductive silicone sensor Neuro-physiological representations


Human-Robot Interaction StudiesControlled studies to better understand the human side of human-robot interaction

A series of studies to understand the human Focus on the important of gaze in interaction Compare physical (robot) verses virtual (animation) Examine arousal and engagement through autonomic responses To better understand the advantages and limitations of physical vs.

animated media

sociable machines

Documents