Re-Using Schematic Grasping Policies

Abstract

It can be difficult to generalize the solutions to grasping and manipulation problems because even small differences in problem context can require qualitatively different solutions. For example, small changes in the shape of an object to be grasped can necessitate different grasp strategies. In this paper, the authors introduce the action schema framework that represents generalized skills in a functional way such that all viable ways of accomplishing a task are represented as instantiations of the generalized skill. They also propose an on-line algorithm for learning how to instantiate the skill in a context-appropriate way. They test this approach with a robotic grocery bagging task in which a dexterous humanoid robot learns to make correct qualitative decisions regarding how to grasp everyday grocery items and drop them in a paper bag.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2005
Accession Number
ADA440343

Entities

People

  • Andrew H. Fagg
  • Robert Platt
  • Roderic A. Grupen

Organizations

  • University of Massachusetts Amherst

Tags

Communities of Interest

  • Autonomy
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Autonomous Systems
  • Climate Change Adaptation
  • Computer Programming
  • Computer Science
  • Computers
  • Control
  • Data Displays
  • Dynamic Programming
  • Equations
  • Expert Systems
  • Learning
  • Probability
  • Robotics
  • Robots
  • Transitions

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Educational Psychology
  • Neural Network Machine Learning.

Technology Areas

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