Measuring Cooperative Robotic Systems Using Simulation-Based Virtual Environment

Abstract

Simulation-based study plays an important role in experimenting, understanding, and evaluating intelligent robotic systems. While robot models can be created and studied in a simulated environment, replacing some of the robot models with their real robot counterparts brings simulation-based study one step closer to the reality. It also provides the flexibility to allow real robots to be experimented within a virtual environment. This capability of robot-in-the-loop simulation is especially useful for large-scale cooperative robotic systems whose complexity and scalability severely limit the possibility for study and evaluation in a physical environment with real robots. This paper presents a simulation-based approach that allows a cooperative robotic system to be effectively evaluated in a virtual environment with combined real and virtual robots. This capability adds to conventional simulation-based study to form an integrated measuring process. An example of robotic convoy system is presented together with metrics to measure the formation coherence of cooperative robotic system. Some preliminary simulation results are presented.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2004
Accession Number
ADA516077

Entities

People

  • Bernard P. Zeigler
  • Xiaolin Hu

Organizations

  • De La Salle University

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Abstracts
  • Artificial Intelligence
  • Computational Science
  • Computer Science
  • Computers
  • Control Systems
  • Detectors
  • Infrared Detectors
  • Intelligent Systems
  • Measurement
  • Resilience
  • Scalability
  • Simulations
  • Software Development
  • Test And Evaluation
  • Virtual Reality
  • Wireless Networks

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computational Modeling and Simulation
  • Military Training and Readiness Simulation

Technology Areas

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