Duo: A Human/Wearable Hybrid for Learning About Common Manipulate Objects

Abstract

Humanoid robots would benefit from a better understanding of common manipulable objects and the human behaviors associated with them. Duo is a human/wearable hybrid that is designed to learn about this important domain of human intelligence by interacting with natural manipulable objects in unconstrained environments. Duo's wearable AI system measures the kinematic configuration of the human's head, torso and dominate arm, while watching the workspace of the human's hand through a head-mounted camera. Duo also requests helpful actions from the human through speech via headphones. This paper presents results on an initial set of behaviors for Duo which lead to high-quality segmentations of common manipulable objects in unconstrained human environments. In Duo, the wearable AI system essentially subsumes the abilities of its cooperative human partner by sharing the human's sensor input and directing a portion of the human's actions. Together, the cooperative human and the wearable AI system can be thought of as constituting a new kind of humanoid robot that complements more traditional, wholly synthetic humanoid robots by allowing researchers to circumvent some of the currently unsolved problems in the field, from dextrous object manipulation to unrestricted mobility.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2002
Accession Number
ADA434730

Entities

People

  • Charles C. Kemp

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Artificial Intelligence Software
  • Computational Science
  • Computer Languages
  • Computer Vision
  • Computers
  • Detection
  • Detectors
  • Human Behavior
  • Human-Machine Interaction
  • Image Recognition
  • Measurement
  • Motion Capture
  • Object Recognition
  • Recognition
  • Robotics
  • Robots

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Criminal Law
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • Autonomy
  • Autonomy - Autonomous System Control