Scalability and Schedulability in Large, Coordinated, Distributed Robot Systems

Abstract

Multiple, independent robot platforms promise significant advantage with respect to robustness and flexibility. However, coordination between otherwise independent robots requires the exchange of information; either implicitly (as in gestural communication), or explicitly (as in message passing in a communication network.) In either case, control processes resident on all coordinated peers must participate in the collective behavior. This paper evaluates the potential to scale such a coupled control framework to many participating individuals, where scalability is evaluated in terms of the schedulability of coupled, distributed control processes. We examine how schedulability affects the scalability of a robot system, and discuss an algorithm used for offline schedulability analysis of a distributed task model. We present a distributed coordinated search task and analyze the schedulability of the designed task structure. We are able to analyze communication delays in the system that put upper bounds on the size of the robot teams. We show that hierarchical methods can be used to overcome the scalability problem. We propose that schedulability analysis should be an integrated part of a multi-robot team design process.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2005
Accession Number
ADA438795

Entities

People

  • Huan Li
  • John D. Sweeney
  • Krithi Ramamritham
  • Roderic A. Grupen

Organizations

  • University of Massachusetts Amherst

Tags

Communities of Interest

  • Autonomy
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Communication Channels
  • Communication Networks
  • Communication Systems
  • Computations
  • Computer Programming
  • Computer Science
  • Computers
  • Control Systems
  • Detectors
  • Line Of Sight
  • Robotic Swarms
  • Robotics
  • Robots
  • Scalability
  • Systems Engineering
  • Wireless Communications

Fields of Study

  • Computer science
  • Engineering

Readers

  • Computer Networking
  • Robotics and Automation.
  • Software Engineering.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Autonomy - Autonomous System Control