Emergent behaviours in non-cooperative biological swarms and bio-inspired strategies shepherding robotic swarms

Abstract

Bees maintain a large separation margin during flying and have demonstrated learning abilities under the limited data on how the environment shapes these margins and the salient factors that mediate behaviours at individual and collective scales. Revealing the dynamics of the mass while performing relevant tasks such as navigating through cluttered environments opens significant opportunities for swarm research. This project addresses key machine perception and autonomy challenges associated with swarm navigation. Navigating a swarm in narrow corridors requires timely precision in the propagation of forces among swarm members to maximize the swarm’s throughput. Using bees as model systems, this project aims to design time-efficient algorithms for the navigation of a mass in a cluttered environment.

Document Details

Document Type
DoD Grant Award
Publication Date
Feb 16, 2024
Source ID
FA23862314033

Entities

People

  • Sridhar Ravi

Organizations

  • Air Force Office of Scientific Research
  • United States Air Force
  • University of New South Wales

Tags

Readers

  • Aerial Unmanned Vehicle Swarm Micro Periodontal Dentistry.
  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Robotics and Automation.

Technology Areas

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