Evolving and Controlling Perimeter, Rendezvous, and Foraging Behaviors in a Computation-Free Robot Swarm

Abstract

Designing and controlling simple collective robot behaviors often requires complex range and bearing sensors and peer-to-peer communication strategies. Recent work studying swarms robots that have no computational power has shown that complex behaviors such as aggregation and clustering items can be produced from extremely simple control policies and sensing capability. We extend previous work on computation-free swarm behaviors and show that it is possible to evolve simple control policies to form a perimeter around a target, rendezvous to a specific location, and perform foraging. We also demonstrate that simple manipulations of the environment provide a form of stigmergic control, whereby these collective behavior can be controlled. The robustness and expressiveness of these behaviors, combined with the simple requirements for control and sensing, demonstrate the feasibility of implementing swarm behaviors at small scales or in extreme environments.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2016
Accession Number
AD1008854

Entities

People

  • Daniel S. Brown
  • Matthew S. Johnson

Organizations

  • Rome Laboratory

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Algorithms
  • Artificial Intelligence
  • Clustering
  • Computations
  • Environment
  • Evolutionary Algorithms
  • Genetic Algorithms
  • Governments
  • Line Of Sight
  • Military Research
  • Multiagent Systems
  • Rendezvous
  • Robotic Swarms
  • Simulations
  • United States Government

Fields of Study

  • Computer science

Readers

  • Aerial Unmanned Vehicle Swarm Micro Periodontal Dentistry.
  • Artificial Intelligence
  • Marine Mammal Biology

Technology Areas

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