Cooperative Multi-Agent Systems in Strong Background Flows

Abstract

Aerial and marine robots operate in a fluid medium which carries significant information not often utilized in path planning and cooperation of such robots. Motivated by this observation, we believe that modeling the macroscopic dynamics of a multi-agent system using the vast and historically grounded knowledge of fluid dynamics will open up many opportunities for a betterunderstanding and subsequent enhancement of the behavior of such multi-agent systems. In addition, by including the dynamics of background flows, significant improvement in mobility, reachability and success rate can be expected in applications such as dynamical target tracking, foreign threat interception, and large-scale environmental sensing. Starting with the consideration of the underlying background flows and the sensor network astwo tightly coupled dynamical systems, we leverage the fluid dynamical description of a system to understand the macroscopic motions of the sensor network as a continuum. We present designs for cooperative control strategies governing both local interactions within the multiagent systems and the emergent swarm behaviors. The proposed fluid-based swarm modelingand control scheme is well-suited for aerial or marine missions including multi-vehicle transportation, cooperative surveillance, collaborative target tracking and capturing, etc. More specifically, we will be focusing on the following research tasks: stability analysis and adaptive control of multi-agent systems modeled as continuous fluids; multi-agent system dynamics coupled with background flow dynamics; experimental evaluation with mobile aerial vehicle swarms.

Document Details

Document Type
DoD Grant Award
Publication Date
Jul 10, 2018
Source ID
N000141812376

Entities

People

  • Kamran Mohseni

Organizations

  • Office of Naval Research
  • United States Navy
  • University of Florida

Tags

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computational Fluid Dynamics (CFD)
  • Distributed Systems and Data Platform Development

Technology Areas

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