A Framework for the Development of Robot Behavior

Abstract

Biological organisms display an astonishing capability to learn new skills and adapt to dynamic environments that far outperforms any computer or robot system. This paper presents an approach to robot skill acquisition that takes concepts from developmental theory to structure the learning problem and provides a mechanism to generate developmental schedules for a robot systems. The approach uses a developmental assembler to construct reusable and temporally extended actions in a sequence. All behavior is initially constructed from a set of innate control laws and events that delineate control decisions are derived from the pattern of (dis)equilibria on a working subset of sensorimotor policies. We show how this architecture can be used to accomplish sequential knowledge gathering and representation tasks and provide examples of developmental learning using a quadrupedal walking robot.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2005
Accession Number
ADA439115

Entities

People

  • Manfred Huber
  • Roderic A. Grupen

Organizations

  • University of Massachusetts Amherst

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Acquisition
  • Computers
  • Control Systems
  • Detectors
  • Environment
  • Hierarchies
  • Information Operations
  • Instructions
  • Learning
  • Massachusetts
  • Reinforcement Learning
  • Robotics
  • Robots
  • Skeleton
  • Systems Biology
  • Universities

Fields of Study

  • Computer science

Readers

  • Neuroscience
  • Robotics and Automation.
  • Theoretical Analysis.

Technology Areas

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