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Life in the Humanoid Robotics Group MIT AI Lab

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Presentation on theme: "Life in the Humanoid Robotics Group MIT AI Lab"— Presentation transcript:

1 Life in the Humanoid Robotics Group MIT AI Lab
Paul Fitzpatrick

2 Our Goal Natural tasking Respond to humanoid cues
Exhibit humanoid cues

3 Our Methodology Integration Social Interaction Embodiment Development
Development: using simple, early behaviors that serve to structure more complex behaviors. Example: the stages of gaze sensitivity and following seen in infants. Also, growing complexity of environment, best If just slightly out of reach. Social interaction: non-hostile world – contigent responses. Embodiment: grounding representations in sensory-motor interaction. Flexibility? Integration: different senses have different strengths and weaknesses but considerable overlap, good to combine them. Development

4 Our Robots

5 Research Issues Our Approaches K n o w i g h a t m e M p b d s C r c f
l u z G x k I v S U y A D L P E - ( , ) Research Issues Our Approaches

6 Research Issues Our Approaches K n o w i g h a t m e M p b d s C r c f
l u z G x k I v S U y A D L P E - ( , ) Research Issues Our Approaches

7 Social Interaction

8 Cynthia Breazeal

9 Showing and Reading

10 Evaluation Metrics Must consider human response as well as robot’s behavior Can people intuitively read and do they naturally respond to Kismet’s social cues? Does Kismet elicit social cues (scaffolding) from the human that could be used to benefit learning? Can Kismet perceive and appropriately respond to these naturally offered social cues? Does the human adapt to the robot, and robot adapt to the human, in a way that benefits the interaction? (entrainment)

11 Research Issues Our Approaches K n o w i g h a t m e M p b d s C r c f
l u z G x k I v S U y A D L P E - ( , ) Research Issues Our Approaches

12 Brian Scassellati

13 Theory of Mind For complex learning tasks the robot needs to
understand what it is the human knows about the world about the robot’s current state understand what the human is doing and why understand what is the human

14 Leslie’s Model ToBY Inanimate Objects Mechanical agency ToMM-1
Actional agency Divides the world into three spheres of causation, each of which is processed by a separate module: Theory of Body (ToBY) – applies naïve physics to objects Theory of Mind Mechanism (ToMM) – applies folk psychology to agents System 1 applies rules of goals and desires System 2 applies rules of belief and knowledge ToMM-2 Attitudinal agency

15 Baron-Cohen’s Model Eye Direction Detector (EDD) Intentionality
Eye-like stimuli Self-Propelled Stimuli Eye Direction Detector (EDD) Intentionality Detector (ID) Dyadic representations (desire, goals) Dyadic Representations (sees) Shared Attention Mechanism (SAM) Requires two types of input stimuli: Eye-like stimuli Self-propelled (animate) stimuli Provides greater detail on the inner workings of Leslie’s ToMM-1 module Proposes that autism is an impairment of either SAM (subgroup A) or ToMM (subgroup B) Theory of Mind Mechanism (ToMM)

16 Pre-attentive filters
Scassellati’s Model Animate Objects ToBY Trajectory Formation Face Finder Visual Attention EDD ID Pre-attentive filters f f SAM Visual Input Visual Input

17 Animacy Detection Animate Inanimate Animate

18 Elastic Collision Expert Acceleration Sign Change Expert
Animacy Experts Straight Line Expert Minimize the sum of the deviations from the mean velocity Constant mass and the inertial system provides the gravity vector Energy Expert Elastic Collision Expert Look for transfer in velocities before and after collision Acceleration Sign Change Expert Look for multiple sign changes in the acceleration

19 Multi-Target Tracking

20 Trajectory Formation t t+1 t+2 t+3

21 Motion Correspondence
(Reid • Cox and Hingorani 1996)

22 Mimicry

23 Faces and Eyes 300 msec 66 msec Locate target In wide field Foveate
Apply Face Filter Software Zoom Feature Extraction 300 msec 66 msec

24 Mimicry

25 Research Issues Our Approaches K n o w i g h a t m e M p b d s C r c f
l u z G x k I v S U y A D L P E - ( , ) Research Issues Our Approaches

26

27 Matthew Marjanović

28 “Trying to make a hard thing easier, By making it much harder.”

29 Virtual Musculature

30 Configurable Musculature

31 Virtual Metabolism

32 Hand

33 Giorgio Metta

34 Reaching

35 Cog’s Sensitive Side

36


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