Enabling Emergent Behaviors in Unmanned Robotic Swarm Systems

Abstract

The goal of this project is to rigorously study the effect of collisions and collision avoidance on emergent behaviors in robotic swarm systems. Many existing works provide theoretical distributed algorithms for such systems but the vast majority of them simply consider point-mass systems where the agents are not able to collide with one another. On the contrary, we are interested in scenarios with large numbers of agents in the swarm in which collisions are considered ‘catastrophic’ in that a collision disables all the participating agents (e.g., miniature unarmored UAVs [9]). We are then concerned with identifying conditions on exactly when enabling such physical constraints disrupts the intended global behavior of the swarm.

Document Details

Document Type
DoD Grant Award
Publication Date
Apr 25, 2019
Source ID
N000141912121

Entities

People

  • Cameron Nowzari

Organizations

  • George Mason University
  • Office of Naval Research
  • United States Navy

Tags

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Theoretical Analysis.
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.

Technology Areas

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