An Implementation of Opportunistic Scheduling for Robotic Assembly

Abstract

The goal of this thesis is to combine computerized vision and artificial intelligence programming in an application of robotic assembly that will use opportunistic scheduling. Opportunistic scheduling is making a schedule based on current opportunities. A robot provided with a vision system has the capability of recognizing random opportunistic events. However, vision systems have many limitations. A heuristic method of taking pictures is developed to improve object recognition reliability. The robot is given basic assembly knowledge using the production rule methodology, and assembly precedence information using a database of partial order sets. Dynamic state information is also maintained by the program. Parts are delivered randomly on conveyor belts. The robot is given the capability of assembling a mix of products and assembling multiple products concurrently. Thus, the robot can assemble a product in any feasible way and schedule an optimal plan according to the random arrival of parts. A user friendly interface with the robot is developed.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1990
Accession Number
ADA231160

Entities

People

  • Allan W. Butler

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Assembly
  • Assembly Lines
  • Computer Programming
  • Computer Vision
  • Computer-Aided Design
  • Computers
  • Databases
  • Fabrication
  • Literature Surveys
  • Manufacturing
  • Object Recognition
  • Prototypes
  • Quality Control
  • Recognition
  • Reliability
  • Training

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Robotics and Automation.
  • Software Engineering

Technology Areas

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