Open Object Recognition for Humanoid Robots

Abstract

Robots must be able to adapt gracefully to frequent and dramatic changes in their workspace if they are to operate successfully in human-centered environments, as opposed to controlled industrial settings. At the MIT Humanoid Robotics Group, investigators are developing methods that permit their robots to deduce the structure of novel activities, adopt the vocabulary appropriate for communication about the task at hand, and learn about the appearance and behavior of unfamiliar objects. The latter ability is discussed in this paper. The humanoid robot, "Cog," uses active exploration to resolve visual ambiguity in its workspace. As Cog accumulates experience, it clusters episodes of object interaction to learn the appearance and properties of novel, unfamiliar objects. This process is called "open object recognition." An operator can then introduce names for objects to facilitate further task-related communication.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2003
Accession Number
ADA434771

Entities

People

  • Paul Fitzpatrick

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Ambiguity
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Clustering
  • Computer Vision
  • Environment
  • Image Recognition
  • Machine Learning
  • Machine Perception
  • Object Recognition
  • Recognition
  • Robotics
  • Robots
  • Visual Servoing

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Artificial Intelligence
  • Computer Vision.

Technology Areas

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