Humanoid Robots as Cooperative Partners for People - PowerPoint PPT Presentation

1 / 27
About This Presentation
Title:

Humanoid Robots as Cooperative Partners for People

Description:

Humanoid Robots as Cooperative Partners for People paper by Breazeal, C., et al.. (2003) MIT Media Lab, Robotic Life Group presentation by K sa M t goston – PowerPoint PPT presentation

Number of Views:144
Avg rating:3.0/5.0
Slides: 28
Provided by: K289
Category:

less

Transcript and Presenter's Notes

Title: Humanoid Robots as Cooperative Partners for People


1
Humanoid Robots as Cooperative Partners for People
  • paper by Breazeal, C., et al.. (2003)
  • MIT Media Lab, Robotic Life Group
  • presentation by Kósa Máté Ágoston
  • cognitive robotics _at_ Rijksuniversiteit Groningen
    2010

2
building socially intelligent robots
  • important implications for how we will be able to
    communicate with, work with, and teach robots in
    the future
  • it is a critical competence for robots that will
    play a useful, rewarding, and long-term role in
    the daily lives of people

3
socially intelligent robot
  • robots that show aspects of human-like social
    intelligence, based on deep models of human
    cognition and social competence
  • contrasted to socially evocative / receptive /
    situated / embedded
  • brings research closer to the hard problem of
    artificial intelligence (in small steps)
  • Fong, T., Nourbakhsh, I. Dautenhahn, K. (2002)

4
socially intelligent robot
  • Why?
  • We anthropomorphize by default
  • Personality lends coherence and consistence to
    behavior (to know someone is to predict his
    actions)
  • Natural learning
  • Scalability reflects in trust and sincerity (for
    when it gets out of hand see Blade Runner, Ridley
    Scott 1982)

5
theory of mind
  • Assumption
  • each participant has a set of mechanisms and
    representations for predicting and interpreting
    others actions, emotions, beliefs, desires, and
    other mental states
  • Derived models
  • joint attention, representation, empathy,
    intersubjectivity, reason (mental states to
    behavior), inference, social reference etc.

6
Collaborative approach vs. ML
  • supervised learning techniques the learning
    algorithm has no a priori knowledge about the
    structure of the state and action spaces, must
    discover any structure that exists on its own
  • needs data, time, relatively stable enviroment
  • problems with generalizing
  • hard to guide for the laic
  • bridges machine learning with HMC

7
Collaborative approach vs. Humans
  • we are innate teachers
  • we have a well-established social signaling ?
  • we have infrastructure
  • we have an affinity towards interdisciplinarity

8
Social Skills
  • reciprocal cooperation is achieved with the goal
    to
  • help the instructor maintain a good mental model
    of the learner
  • help the learner leverage from instruction and
    guidance to build the appropriate task models,
    representations, associations, etc.
  • test of abilities the button task

9
Social Skills
  • Communication skill
  • Deictic reference
  • Joint attention
  • Mutual beliefs

10
Communication
  • Conversational policies
  • Cohen et. al. (1990) argue that much of
    task-oriented dialog can be understood in terms
    of Joint Intention Theory
  • Modeled after analysis of master-novice task
  • Turn-taking skills
  • Modeled after human model, very robust
  • Envelope displays (para-linguistic cues)

11
Communication
  • same goal and the same plan of execution
  • different abilities, tools, partial knowledge
    and different beliefs referring to the state of
    the goal
  • communication is necessary to mobilize the
    potential
  • Conversational policies
  • Cohen et. al. (1990) argue that much of
    task-oriented dialog can be understood in terms
    of Joint Intention Theory
  • Modeled after analysis of master-novice task
  • Turn-taking skills
  • Modeled after human model, very robust
  • Envelope displays (para-lingvistic cues)

12
Communication
  • same goal and the same plan of execution
  • different abilities, tools, partial knowledge
    and different beliefs referring to the state of
    the goal
  • communication is necessary to mobilize the
    potential
  • Conversational policies
  • Cohen et. al. (1990) argue that much of
    task-oriented dialog can be understood in terms
    of Joint Intention Theory
  • Modeled after analysis of master-novice task
  • Turn-taking skills
  • Modeled after human model, very robust
  • Envelope displays (para-lingvistic cues)

Organizational markers Elaborations Clarifications
Confirmations Referential elaborations
Confirmations of successful identification
13
Communication
  • Conversational policies
  • Cohen et. al. (1990) argue that much of
    task-oriented dialog can be understood in terms
    of Joint Intention Theory
  • Modeled after analysis of master-novice task
  • Turn-taking skills
  • Modeled after human model, very robust
  • Envelope displays (para-linguistic cues)

14
Deictic reference
  • Estimating gaze via estimating head-pose
  • pan / tilt / rotation
  • objects in 3D spatial map projected on gaze
    vector
  • camera on the wall (panoramic view)
  • Pointing
  • background and depth map extraction
  • candidates fit to ellipse, then presence of
    pointing finger is analyzed (kurtosis)
  • stereo camera ceiling-mounted (birds eye view)

15
Deictic reference
  • Estimating gaze via estimating head-pose
  • pan / tilt / rotation
  • objects in 3D spatial map projected on gaze
    vector
  • camera on the wall (panoramic view)
  • Pointing
  • background and depth map extraction
  • candidates fit to ellipse, then presence of
    pointing finger is analyzed (kurtosis)
  • stereo camera ceiling-mounted (birds eye view)

16
Deictic reference
  • Estimating gaze via estimating head-pose
  • pan / tilt / rotation
  • objects in 3D spatial map projected on gaze
    vector
  • camera on the wall (panoramic view)
  • Pointing
  • background and depth map extraction
  • candidates fit to ellipse, then presence of
    pointing finger is analyzed (kurtosis)
  • stereo camera ceiling-mounted (birds eye view)

17
Joint Attention
  • seeing vs. attending (in baby humans 7-9 months)
  • referential looking (in baby humans 6-18 months)
  • proto-declarative pointing (in b.h. 9-12 months)
  • exploiting all these at 14 months of age (in
    b.h.)
  • two entities looking at the same thing is not
    necessarily joint attention (necessary-not-suff)
  • updating mutual belief with a common referent is
    closer to the human-human model

18
(No Transcript)
19
(No Transcript)
20
Joint Attention
  • To keep in mind
  • Attention focus (what gets the attention)
  • Referent focus (the subject of communication)
  • Saliency determines a list, not a particular
    object
  • perceptual/internal/socially cued saliency
  • Decay of saliency
  • Leonardos model of own foci
  • Leonardos model of instructors foci

21
Beliefs
  • humans around the age of 3 note difference
    between perception and belief
  • temporal integration of perceptual input
  • (composite instances of real-world objects)
  • percept tree gt snapshot gt belief .
  • classification gt data structure gt create/update

22
Beliefs
  • humans around the age of 3 note difference
    between perception and belief
  • temporal integration of perceptual input
  • (composite instances of real-world objects)
  • percept tree gt snapshot gt belief .
  • classification gt data structure gt create/update
  • when the robot shares a belief with a human, the
    belief gets labeled as mutual belief
  • humans attentional and referent focus are
    updated for the belief concerned

23
Learning
  • From internal demonstration
  • telemetry suit ?
  • robot interpolates exemplars using a dynamically
    weighted blend of the recorded button pressing
    trajectories
  • Names of things
  • social cue feedback

24
Learning
  • Task structure
  • task is either a (sub)task or an action,
    hierarchically organized
  • constraints exist as actions (currently used for
    sequential constraints but are expandable)
  • task goals are more than the sum of (sub)task
    goals
  • a goal can be either a
  • state-change in world (attain a state)
  • performance (just do it)
  • Natural instruction

25
Performing in collaboration
  • possible because of the goal-oriented approach
    (and the turn-taking implementation)
  • communication of robots perceived SoW and
    intention leads to common ground which is the
    basis of joint intention/attention/planning
  • knowledge of own abilities, negotiation of task
    with human
  • importance of gestural cues during collaboration

26
Video time
27
Discussion
  • Knowing what matters
  • restraining search-space by saliency
  • temporal cues joint attention
  • Knowing what to try
  • collaboration contrasted with imitation and
    experiment
  • Knowing how to recognize success/faliure
  • goal types change desired/performance, goal
    progress
  • Knowing how to explore
  • Knowing how to leverage the provided structure
  • experienced demonstration, mo generally social
    context
Write a Comment
User Comments (0)
About PowerShow.com