Sequential Task Execution in a Minimalist Distributed Robotic System

Abstract

The collective execution of a single task, such as foraging or clustering, has received considerable research attention in the minimalist distributed robotic systems (MDRS) community. In contrast, achievement of sequential tasks by MDRS has so far been considered in only a handful of studies. Sequential task execution requires a collective system to carry out a task, and then, in a coordinated fashion, move on to another task. This paper describes work in controlling a minimalist distributed robotic system in sequential task execution. We present two MDRS algorithms for sequential task execution in the foraging task domain, and validate them experimentally in simulation. One of the algorithms uses temporal behavior activation, the other makes use of probabilistic behavior activation. Both are effective in the partially-observable, non-stationary environments were tested them in, and their relative strengths are compared analytically.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2005
Accession Number
ADA438555

Entities

People

  • Chris Jones
  • Maja Matarić

Organizations

  • University of Southern California

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Automata Theory
  • Autonomous Systems
  • Collision Avoidance
  • Computer Science
  • Global Positioning Systems
  • Probability
  • Random Variables
  • Random Walk
  • Robotics
  • Robots
  • Self Organizing Systems
  • Simulations
  • Stigmergy
  • Swarm Intelligence
  • Test And Evaluation

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Instructional Design and Training Evaluation.
  • Statistical inference.

Technology Areas

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